Prior work demonstrates the importance of introducing young children to programming and engineering content before gender stereotypes are fully developed and ingrained in later years. However, very little research on gender and early childhood technology interventions exist. This pilot study looks at N=45 children in kindergarten through second grade who completed an eight-week robotics and programming curriculum using the KIWI robotics kit. KIWI is a developmentally appropriate robotics construction set specifically designed for use with children ages 4 to 7 years old. Qualitative pre-interviews were administered to determine whether participating children had any gender-biased attitudes toward robotics and other engineering tools prior to using KIWI in their classrooms. Post-tests were administered upon completion of the curriculum to determine if any gender differences in achievement were present. Results showed that young children were beginning to form opinions about which technologies and tools would be better suited for boys and girls. While there were no significant differences between boys and girls on the robotics and simple programming tasks, boys performed significantly better than girls on the advanced programming tasks such as, using repeat loops with sensor parameters. Implications for the design of new technological tools and curriculum that are appealing to boys and girls are discussed.

The Hour of Code is a one-hour introduction to computer science organized by Code.org, a non-profit dedicated to expanding participation in computer science. This study investigated the impact of the Hour of Code on students’ attitudes towards computer programming and their knowledge of programming. A sample of undergraduate students from two universities was selected to participate. Participants completed an Hour of Code tutorial as part of an undergraduate course. An electronic questionnaire was implemented in a pre-survey and post-survey format to gauge the change in student attitudes toward programming and their programming ability. The findings indicated the positive impact of the Hour of Code tutorial on students’ attitude toward programming. However, the students’ programming skills did not significantly change. The authors suggest that a deeper alignment of marketing, teaching, and content would help sustain the type of initiative exemplified by the Hour of Code.

This paper examines how to leverage the design studio learning environment throughout long-term Digital Design education in order to support students to progress from tactical, well-defined, device-centric routine design, to confidently design sustainable solutions for strategic, complex, problems for a wide range of devices and platforms in the digital space. We present a framework derived from literature on design, creativity, and theories on learning that: (a) implements a theory of formal learning sequences as a user-centered design process in the studio; and (b) describes design challenge progressions in the design studio environment modeled in seven dimensions. The framework can be used as a tool for designing, evaluating, and communicating course progressions within – and between series of – design studio courses. This approach is evaluated by implementing a formal learning sequence framework in a series of design studio courses that progress in an undergraduate design-oriented Informatics program. Reflections from students, teachers, and external clients indicate high student motivation and learning goal achievement, high teacher satisfaction and skill development, and high satisfaction among external clients.

Aim/Purpose: From an idea of lifelong-learning-for-all to a phenomenon affecting higher education, Massive Open Online Courses (MOOCs) can be the next step to a truly universal education. Indeed, MOOC enrolment rates can be astoundingly high; still, their completion rates are frequently disappointingly low. Nevertheless, as courses, the participants’ enrolment and learning within the MOOCs must be considered when assessing their success. In this paper, the authors’ aim is to reflect on what makes a MOOC successful to propose an analysis framework of MOOC success factors. Background: A literature review was conducted to identify reported MOOC success factors and to propose an analysis framework. Methodology: This literature-based framework was tested against data of a specific MOOC and refined, within a qualitative interpretivist methodology. The data were collected from the ‘As alterações climáticas nos média escolares - Clima@EduMedia’ course, which was developed by the project Clima@EduMedia and was submitted to content analysis. This MOOC aimed to support science and school media teachers in the use of media to teach climate change Contribution: By proposing a MOOC success factors framework the authors are attempting to contribute to fill in a literature gap regarding what concerns criteria to consider a specific MOOC successful. Findings: This work major finding is a literature-based and empirically-refined MOOC success factors analysis framework. Recommendations for Practitioners: The proposed framework is also a set of best practices relevant to MOOC developers, particularly when targeting teachers as potential participants. Recommendation for Researchers: This work’s relevance is also based on its contribution to increasing empirical research on MOOCs. Impact on Society: By providing a proposal of a framework on factors to make a MOOC successful, the authors hope to contribute to the quality of MOOCs. Future Research: Future work should refine further the proposed framework, by in testing it against data collected in other MOOCs.

Aim/Purpose: Compared student academic performance on specific course requirements in a C# programming course across three instructional approaches: traditional, online, and flipped. Background: Addressed the following research question: When compared to the online and traditional instructional approaches, does the flipped instructional approach have a greater impact on student academic performance with specific course requirements in a C# programming course? Methodology: Quantitative research design conducted over eight 16-week semesters among a total of 271 participants who were undergraduate students en-rolled in a C# programming course. Data collected were grades earned from specific course requirements and were analyzed with the nonparametric Kruskal Wallis H-Test using IBM SPSS Statistics, Version 23. Contribution: Provides empirical findings related to the impact that different instructional approaches have on student academic performance in a C# programming course. Also describes implications and recommendations for instructors of programming courses regarding instructional approaches that facilitate active learning, student engagement, and self-regulation. Findings: Resulted in four statistically significant findings, indicating that the online and flipped instructional approaches had a greater impact on student academic performance than the traditional approach. Recommendations for Practitioners: Implement instructional approaches such as online, flipped, or blended which foster active learning, student engagement, and self-regulation to increase student academic performance. Recommendation for Researchers: Build upon this study and others similar to it to include factors such as gender, age, ethnicity, and previous academic history. Impact on Society: Acknowledge the growing influence of technology on society as a whole. Higher education coursework and programs are evolving to encompass more digitally-based learning contexts, thus compelling faculty to utilize instructional approaches beyond the traditional, lecture-based approach. Future Research: Increase the number of participants in the flipped instructional approach to see if it has a greater impact on student academic performance. Include factors beyond student academic performance to include gender, age, ethnicity, and previous academic history.

Aim/Purpose: Improving public schools is a focus of federal legislation in the United States with much of the burden placed on principals. However, preparing principals for this task has proven elusive despite many changes in programming by institutions of higher learning. Emerging technologies that rely on augmented and virtual realities are posited to be powerful pedagogical tools for closing this gap. Background: This study investigated the effects of immersive simulation technologies on principals’ self-efficacy after treatment and the perceived significance of the design of the immersive simulation experience as an effective tool for adult learners. Methodology: The investigator employed a multiple-methods study that relied on a purposive sample of graduate students enrolled in educational leadership programs at two small universities in the southeastern United States. Participants completed a two-hour module of immersive simulation designed to facilitate transfer of knowledge to skills thereby increasing their self-efficacy. Contribution: This paper contributes to a small body of literature that examines the use of immersive simulation to prepare aspiring principals. Findings: The findings indicate moderate effect sizes in changes in self-efficacy, positive attitudes toward immersive simulation as a pedagogical tool, and significance in the design of immersive simulation modules. This suggests that immersive simulation, when properly designed, aids principals in taking action to improve schools. Recommendations for Practitioners: Educational leadership programs might consider the use of immersive simulations to enhance principals’ ability to meet the complex demands of leading in the 21st century. Impact on Society: Principals may be more adept at improving schools if preparation programs provided consistent opportunities to engage in immersive simulations. Future Research: Future research should be conducted with larger sample sizes and longitudinally to determine the effectiveness of this treatment.

Aim/Purpose: As smartphones proliferate, many different platforms begin to emerge. The challenge to developers as well as IS educators and students is how to learn the skills to design and develop apps to run on cross-platforms. Background: For developers, the purpose of this paper is to describe an alternative to the complex native app development. For IS educators and students, the paper provides a feasible way to learn and develop fully functional mobile apps without technical burdens. Methodology: The methods used in the development of browser-based apps is prototyping. Our proposed approach is browser-based, supports cross-platforms, uses open-source standards, and takes advantage of “write-once-and-run-anywhere” (WORA) concept. Contribution: The paper illustrates the application of the browser-based approach to create a series of browser apps without high learning curve. Findings: The results show the potentials for using browser app approach to teach as well as to create new apps. Recommendations for Practitioners : Our proposed browser app development approach and example would be useful to mobile app developers/IS educators and non-technical students because the source code as well as documentations in this project are available for downloading. Future Research: For further work, we discuss the use of hybrid development framework to enhance browser apps.

Aim/Purpose: The aims of this study were to investigate the feasibility of automatic assessment of programming tasks and to compare manual assessment with automatic assessment in terms of the effect of the different assessment methods on the marks of the students. Background: Manual assessment of programs written by students can be tedious. The assistance of automatic assessment methods might possibly assist in reducing the assessment burden, but there may be drawbacks diminishing the benefits of applying automatic assessment. The paper reports on the experience of a lecturer trying to introduce automated grading. Students’ solutions to a practical Java programming test were assessed both manually and automatically and the lecturer tied the experience to the unified theory of acceptance and use of technology (UTAUT). Methodology: The participants were 226 first-year students registered for a Java programming course. Of the tests the participants submitted, 214 were assessed both manually and automatically. Various statistical methods were used to compare the manual assessment of student’s solutions with the automatic assessment of the same solutions. A detailed investigation of reasons for differences was also carried out. A further data collection method was the lecturer’s reflection on the feasibility of automatic assessment of programming tasks based on the UTAUT. Contribution: This study enhances the knowledge regarding benefits and drawbacks of automatic assessment of students’ programming tasks. The research contributes to the UTAUT by applying it in a context where it has hardly been used. Furthermore, the study is a confirmation of previous work stating that automatic assessment may be less reliable for students with lower marks, but more trustworthy for the high achieving students. Findings: An automatic assessment tool verifying functional correctness might be feasible for assessment of programs written during practical lab sessions but could be less useful for practical tests and exams where functional, conceptual and structural correctness should be evaluated. In addition, the researchers found that automatic assessment seemed to be more suitable for assessing high achieving students. Recommendations for Practitioners: This paper makes it clear that lecturers should know what assessment goals they want to achieve. The appropriate method of assessment should be chosen wisely. In addition, practitioners should be aware of the drawbacks of automatic assessment before choosing it. Recommendation for Researchers: This work serves as an example of how researchers can apply the UTAUT theory when conducting qualitative research in different contexts. Impact on Society: The study would be of interest to lecturers considering automated assessment. The two assessments used in the study are typical of the way grading takes place in practice and may help lecturers understand what could happen if they switch from manual to automatic assessment. Future Research: Investigate the feasibility of automatic assessment of students’ programming tasks in a practical lab environment while accounting for structural, functional and conceptual assessment goals.

Aim/Purpose: The goal of this paper is to examine whether having female robotics teachers positively impacts girls’ performance on programming and robotics tasks Background: Women continue to be underrepresented in the technical STEM fields such as engineering and computer science. New programs and initiatives are needed to engage girls in STEM beginning in early childhood. The goal of this work is to explore the impact of teacher gender on young children’s mastery of programming concepts after completing an introductory robotics program. Methodology: A sample of N=105 children from six classrooms (2 Kindergarten, 2 first grade, and 2 second grade classes) from a public school in Somerville, Massachusetts, participated in this research. Children were taught the same robotics curriculum by either an all-male or all-female teaching team. Upon completion of the curriculum, they completed programming knowledge assessments called Solve-Its. Comparisons between the performance of boys and girls in each of the teaching groups were made. Findings: This paper provides preliminary evidence that having a female instructor may positively impact girls’ performance on certain programming tasks and reduce the number of gender differences between boys and girls in their mastery of programming concepts. Recommendations for Practitioners: Practitioners should expose children to STEM role-models from a variety of backgrounds, genders, ethnicities, and experiences. Future Research: Researchers should conduct future studies with larger samples of teachers in order to replicate the findings here. Additionally, future research should focus on collecting data from teachers in the form of interviews and surveys in order to find out more about gender-based differences in teaching style and mentorship and the impact of this on girls' interest and performance in STEM.

Aim/Purpose: This study was aimed at enhancing students’ learning of software engineering methods. A collaboration between the Computer Science, Business Management, and Product Design programs was formed to work on actual projects with real clients. This interdisciplinary form of collaboration simulates the realities of a diverse Software Engineering team. Background: A collaborative approach implemented through projects has been the established pedagogy for introducing the Software Engineering course to undergraduate Computer Science students. The collaboration, however, is limited to collaboration among Computer Science students and their clients. This case study explored an enhancement to the collaborative approach to project development by integrating other related disciplines into the project development framework; hence, the Interdisciplinary Approach. Methodology: This study adopted the case method approach. An interdisciplinary service innovation activity was proposed to invite other disciplines in the learning process of the computer science students. The agile methodology Scrum was used as the software development approach during project development. Survey data were collected from the students to establish (a) their perception of the interdisciplinary approach to project development; (b) the factors that influenced success or failure of their team to deliver the project; and (c) the perceived skills or knowledge that they acquired from the interdisciplinary approach. Analysis of data followed a mixed method approach. Contribution: The study improved the current pedagogy for Software Engineering education by integrating other related disciplines into the software project development framework. Findings: Data collected showed that the students generally accepted the interdisciplinary approach to project development. Factors such as project relevance, teamwork, time and schedule, and administration support, among others, affect team performance towards project completion. In the case of the Computer Science students, results show that students have learned skills during the experience that, as literature reveal, can only be acquired or mastered in their future profession as software engineers. Recommendations for Practitioners: The active collaboration of the industry with the University and the involvement of the other related courses in teaching software engineering methods are critical to the development of the students, not only in learning the methodology but also as a working professional. Recommendation for Researchers: It is interesting to know and eventually understand the interactions between interdisciplinary team members in the conduct of Software Engineering practices while working on their projects. More specifically, what creative tensions arise and how do the interdisciplinary teams handle the discourse? Impact on Society: This study bridges the gap between how Software Engineering is taught in the university and how Software Engineering teams work in real life. Future Research: Future research is targeted at refining and elaborating the elements of the interdisciplinary framework presented in this paper towards an integrated course module for Software Engineering education.

Aim/Purpose: The purpose of this exploratory case study was to understand how teachers, working with English Language Learners (ELLs), expanded their knowledge and instructional practices as they implemented a one-to-one iPad® program. Background: English Language Learners experience linguistic, cultural, and cognitive shifts that can be challenging, and at times lead to isolation for ELLs. While technology can be engaging, devices alone do not shift instructional practices, nor lead to student learning. Technology must be leveraged through shifts to pedagogical practice and linked thoughtfully to content goals. Methodology: This research was conducted through a qualitative case study of educators at an international school. Contribution: This study describes promising pedagogical practices for leveraging 1:1 mobile devices for ELLs. Findings: iPads can be a support for ELL students. One-to-one iPads allowed teachers to experiment with new pedagogical approaches, but this development varies greatly between teachers. During the 1:1 implementation there were challenges reported. Recommendations for Practitioners: In order to mitigate some of these challenges, and build on the success of this study, the researcher suggests developing a common vision for technology integration, using collaborative models of ELL teaching, and investing in professional development. Recommendation for Researchers: Researchers should continue to document and observe the learning outcomes of ELL students in 1:1 environments, including an experimental study. Impact on Society: ELLs can benefit from 1:1 technology, and new pedagogical practices. For teachers to implement these new practices conversations on philosophy, engagement with families, and consistent professional development. Future Research: Future research can continue to expand the population of ELL students in 1:1 mobile learning environments; and the most powerful pedagogical practices.

Aim/Purpose: This paper presents a data mining approach for analyzing responses to advanced declarative programming questions. The goal of this research is to find a model that can explain the results obtained by students when they perform exams with Constructed Response questions and with equivalent Multiple-Choice Questions. Background: The assessment of acquired knowledge is a fundamental role in the teaching-learning process. It helps to identify the factors that can contribute to the teacher in the developing of pedagogical methods and evaluation tools and it also contributes to the self-regulation process of learning. However, better format of questions to assess declarative programming knowledge is still a subject of ongoing debate. While some research advocates the use of constructed responses, others emphasize the potential of multiple-choice questions. Methodology: A sensitivity analysis was applied to extract useful knowledge from the relevance of the characteristics (i.e., the input variables) used for the data mining process to compute the score. Contribution: Such knowledge helps the teachers to decide which format they must consider with respect to the objectives and expected students results. Findings: The results shown a set of factors that influence the discrepancy between answers in both formats. Recommendations for Practitioners: Teachers can make an informed decision about whether to choose multiple-choice questions or constructed-response taking into account the results of this study. Recommendation for Researchers: In this study a block of exams with CR questions is verified to complement the area of learning, returning greater performance in the evaluation of students and improving the teaching-learning process. Impact on Society: The results of this research confirm the findings of several other researchers that the use of ICT and the application of MCQ is an added value in the evaluation process. In most cases the student is more likely to succeed with MCQ, however if the teacher prefers to evaluate with CR other research approaches are needed. Future Research: Future research must include other question formats.

Aim/Purpose: The study examined types of errors made by novice programmers in different Java concepts with students of different ability levels in programming as well as the perceived causes of such errors. Background: To improve code writing and debugging skills, efforts have been made to taxonomize programming errors and their causes. However, most of the studies employed omnibus approaches, i.e. without consideration of different programing concepts and ability levels of the trainee programmers. Such concepts and ability specific errors identification and classifications are needed to advance appropriate intervention strategy. Methodology: A sequential exploratory mixed method design was adopted. The sample was an intact class of 124 Computer Science and Engineering undergraduate students grouped into three achievement levels based on first semester performance in a Java programming course. The submitted codes in the course of second semester exercises were analyzed for possible errors, categorized and grouped across achievement level. The resulting data were analyzed using descriptive statistics as well as Pearson product correlation coefficient. Qualitative analyses through interviews and focused group discussion (FGD) were also employed to identify reasons for the committed errors. Contribution:The study provides a useful concept-based and achievement level specific error log for the teaching of Java programming for beginners. Findings: The results identified 598 errors with Missing symbols (33%) and Invalid symbols (12%) constituting the highest and least committed errors respec-tively. Method and Classes concept houses the highest number of errors (36%) followed by Other Object Concepts (34%), Decision Making (29%), and Looping (10%). Similar error types were found across ability levels. A significant relationship was found between missing symbols and each of Invalid symbols and Inappropriate Naming. Errors made in Methods and Classes were also found to significantly predict that of Other Object concepts. Recommendations for Practitioners: To promote better classroom practice in the teaching of Java programming, findings for the study suggests instructions to students should be based on achievement level. In addition to this, learning Java programming should be done with an unintelligent editor. Recommendations for Researchers: Research could examine logic or semantic errors among novice programmers as the errors analyzed in this study focus mainly on syntactic ones. Impact on Society: The digital age is code-driven, thus error analysis in programming instruction will enhance programming ability, which will ultimately transform novice programmers into experts, particularly in developing countries where most of the software in use is imported. Future Research: Researchers could look beyond novice or beginner programmers as codes written by intermediate or even advanced programmers are still not often completely error free.

Aim/Purpose: In this study, the researchers investigated whether the out-of-class learning approach could help the students to attain any valuable learning outcomes for cybersecurity learning and could enhance the perceived value of cybersecurity education among the students. Background: Cybersecurity learning poses challenges for its students to learn a complicated subject matter and the students may be intimidated by the challenging courses in cybersecurity programs. Therefore, it is essential for the faculty members to devise some mechanisms to promote cybersecurity learning to increase its student retention. The mechanism suggested by this study was the out-of-class learning approach. Methodology: The researchers in this study employed a content analysis and adopted a semiotic method to analyze qualitative data. The researchers also conducted crosstabulation analyses using chi-square tests to detect the significant differences in the emerging learning outcomes from the two different out-of-class learning activities investigated in this study. Contribution: This study addressed the difficulty of cybersecurity education and proposed a viable mechanism to promote the student learning in such a complicated subject matter. Findings: For cybersecurity education, the out-of-class learning approach is a viable pedagogical mechanism that could lead the students to several learning outcomes, including connecting them to the real-life scenarios related to the cybersecurity profession, guiding them to their career choices and development, stimulating their intellectual growth, creating their justification of learning, and raising their cybersecurity awareness. Recommendations for Practitioners: The instructors of any cybersecurity programs should incorporate some out-of-class learning activities into the courses in their programs, especially the introductory-level courses. Additionally, it is important to coordinate the out-of-class learning activities with the in-class lessons to enable the students to justify what they have learned in their classrooms and motivate them to learn more. Recommendation for Researchers: Researchers could look beyond in-class learning and laboratory learning to investigate the impacts of out-of-class learning activities on cybersecurity education to help the students to attain better learning outcomes. Impact on Society: By promoting cybersecurity education, universities and colleges could attain a higher retention rate of the students in their cybersecurity programs. The higher retention rate of the students in cybersecurity programs would help to ease the critical shortage of cybersecurity talent. Future Research: Future research could explore the impacts of other out-of-class learning activities on cybersecurity learning; for example: job shadowing, attending cybersecurity conferences, internship, developing cybersecurity systems or tools for actual customers, working on cybersecurity research with faculty members. Additionally, future studies could investigate the effects of the out-of-class learning approach on promoting other academic programs that are characterized by intensely complex and technical nature, similar to cybersecurity programs.

Aim/Purpose: Although many computer science measures have been proposed, visualizing individual students’ capabilities is difficult, as those measures often rely on specific tools and methods or are not graded. To solve these problems, we propose a rubric for measuring and visualizing the effects of learning computer programming for elementary school students enrolled in computer science education (CSE), which is independent of the programming language being used. Background: In this research, we proposed a rubric based on existing CSE standards and criteria having a programming education-learning goal. We then applied this rubric to actual lessons to visualize the educational effects. Methodology: The proposed new rubric for teaching computer programming, based on existing standards and criteria, was applied to fourth- and sixth-grade students in Japan. We assessed which skills were cultivated through quizzes before and after the teaching. Contribution: This paper contributes on how to make and utilize a rubric for programming education in computer science. We evaluated and visualized the proposed rubric’s learning effects on children and found that our proposed rubrics are independent of any particular method or tool. Findings: The results of this survey are twofold: (1) we proposed a rubric of programming education in computer science, independent of the programming tools used and (2) we succeeded in visualizing students’ learning stages by applying the proposed rubric to programming education conducted in a Japanese elementary school. Recommendations for Practitioners: Evaluating educational effects in CSE is important. In particular, graded assessments of learner abilities can reveal individual characteristics. This research is useful for assessing CSE because it focuses specifically on programming education. Recommendation for Researchers: The rubric’s suggestions and quality improvements in CSE help learners assess their learning progress and will clarify the cultivated computer science skills. Impact on Society: This research evaluates CSE based on a rubric in the programming education field. Future Research: Future work is needed to improve the proposed rubric’s quality and relevance. Also, this rubric should be applied to many classes to increase the number of evaluations and analyses.

Aim/Purpose: The purpose of this study is to develop an efficient methodology that can assist the evaluators in assessing a variable number of individuals that are working in groups and guarantee that the assessment is dependent on the group members’ performance and contribution to the work developed. Background: Collaborative work has been gaining more popularity in academic settings. However, group assessment needs to be performed according to each individual’s performance. The problem rests on the need to distinguish each member of the group in order to provide fair and unbiased assessments. Methodology: Design Science Research methodology supported the design of a framework able to provide the evaluator with the means to distinguish individuals in a workgroup and deliver fair results. Hevner’s DSR guidelines were fulfilled in order to describe WebAVALIA. To evaluate the framework, a quantitative study was performed and the first results are presented. Contribution: This paper provides a methodological solution regarding a fair evaluation of collaborative work through a tool that allows its users to perform their own assessment and peer assessment. These are made accordingly to the user’s perspectives on the performance of each group member throughout the work development. Findings: The first analysis of the results indicates that the developed method provides fairness in the assessment of group members, delivering a distinction amongst individuals. Therefore, each group member obtains a mark that corresponds to their specific contribution to the workgroup. Recommendations for Practitioners: For those who intend to apply this workgroup assessment method, it is relevant to raise student awareness about the methodology that is going to be used. That is, all the functionalities and steps in WebAVALIA have to be thoroughly explained before beginning of the project. Then, the evaluators have to decide about the students’ intermediate voting, namely if the evaluator chooses or not to publish student results throughout the project’s development. If there is the decision to display these intermediate results, the evaluator must try to encourage collaboration among workgroup members, instead of competition. Recommendation for Researchers: This study explores the design and development of an e-assessment tool – WebAVALIA. In order to assess its feasibility, its use in other institutions or contexts is recommended. The gathering of user opinions is suggested as well. It would then be interesting to compare the findings of this study with the results from other experimentations Impact on Society: Sometimes, people develop a rejection of collaborative work because they feel exploited due to the biased evaluation results. However, the group members assessment distinction, according to each one’s performance, may give each individual a sense of fairness and reward, leading to an openness/willingness towards collaborative work. Future Research: As future work, there are plans to implement the method in other group assessment contexts – such as sports and business environments, other higher education institutions, technical training students – in other cultures and countries. From this myriad of contexts, satisfaction results would be compared. Other future plans are to further explore the mathematical formulations and the respective WebAVALIA supporting algorithms.

Aim/Purpose: This study reports the outcome of how a first pilot semester introductory programming course was designed to provide tangible evidence in support of the concept of Student Ownership of Learning (SOL) and how the outcomes of this programming course facilitate effective student learning. Background: Many instructors want to create or redesign their courses to strengthen the relationship between teaching and learning; however, the researchers of this study believe that the concept of Student Ownership of Learning (SOL) connects to student engagement and achievement in the classroom setting. The researchers redesigned the introductory programming course to include valuable teaching methods to increase Student Ownership of Learning and constructive approaches such as making students design an authentic mobile app project as individuals, partners, or within teams. The high quality of students’ projects positioned them as consultants to the university IT department. Methodology: This paper employs a case study design to construct a qualitative research method as it relates to the phenomenon of the study’s goals and lived experiences of students in the redesigned introductory programming course. The redesigned course was marketed to students as a new course with detailed description and elements that were different from the traditional computer science introductory programming course requirement. The redesigned introductory programming course was offered in two sections: one section with 14 registered students and the other section with 15 registered students. One faculty member instructed both sections of the course. A total of 29 students signed up for the newly redesigned introductory programming course, more than in previous semesters, but two students dropped out within the first two weeks of the redesigned course making a total of 27 students. The redesigned coursework was divided into two parts of the semester. The first part of the semester detailed description and elements of the coursework including a redesigned approach with preparation for class, a quiz, and doing homework in class, which gives students control of decisions whenever possible; and working with each other, either with a partner or in a team. The second part of the semester focuses on students designing a non-trivial working mobile app and presenting their developing mobile app at a significant public competition at the end of the semester. Students developed significantly complex mobile apps and incorporated more complex functionality in their apps. Both Management Information System (MIS) major students and Computer Science major students were in the same course despite the fact that MIS students had never taken a programming course before; however, the Computer Science students had taken at least one course of programming. Contribution: This study provides a practical guide for faculty members in Information Technology programs and other faculty members in non-Computer Science programs to create or redesign an introductory course that increases student engagement and achievement in the classroom based on the concept of Student Ownership of Learning (SOL). This study also deepens the discussion in curriculum and instruction on the value to explore issues that departments or programs should consider when establishing coursework or academic programs. Findings: This study found two goals evidently in support to increase Student Ownership of Learning (SOL). The first goal (Increase their ownership of learning SOL) showed that students found value in the course contents and took control of their learning; therefore, the faculty no longer had to point out how important different programming concepts were. The students recognized their own learning gap and were excited when shown a programming concept that addressed the gap. For example, student comments were met with “boy, we can really use this in our app” instead of comments about how complex they were. The coursework produced a desired outcome for students as they would get the knowledge needed to make the best app that they could. The second goal (Develop a positive attitude toward the course) showed positive results as students developed a more positive attitude towards the course. Student actions in the classroom strongly reflected a positive attitude. Attendance was almost 100% during the semester even though no points for attendance were given. Further evidence of Student Ownership of Learning and self-identity was students’ extensive use of the terminology and concept of the course when talking to others, especially during the public competition. Students were also incorporating their learning into their identities. For example, teams became known by their app such as the Game team, the Recipe team, and the Parking team. One team even made team t-shirts. Another exciting reflection of the Student Ownership of Learning which occurred was the learning students did by themselves. Recommendations for Practitioners: Practitioners can share best practices with faculty in different departments, programs, universities, and educational consultants to cultivate the best solution for Student Ownership of Learning based on student engagement and achievement in the classroom setting. Recommendation for Researchers: Researchers can explore different perspectives with scholars and practitioners in various disciplinary fields of study to create or redesign courses and programs to reflect Student Ownership of Learning (SOL). Impact on Society: Student Ownership of Learning is relevant for faculty and universities to incorporate in the creation or redesigning of coursework in academic programs. Readers can gain an understanding that student engagement and achievement are two important drivers of Student Ownership of Learning (SOL) in the classroom setting. Future Research: Practitioners and researchers could follow-up in the future with a study to provide more understanding and updated research information from different research samples and hypotheses on Student Ownership of Learning (SOL).

Aim/Purpose: Multi-threaded software design is considered to be difficult, especially to novice programmers. In this study, we explored how students cope with a task that its solution requires a multi-threaded architecture to achieve optimal runtime. Background: An efficient exploit of multicore processors architecture requires computer programs that use parallel programming techniques. However, parallel programming is difficult to understand and apply by novice programmers. Methodology: The students had to address a two-stage problem: (1) design an optimal runtime solution to a given problem with no additional instructions; and (2) provide an optimal runtime multi-threaded design to the same problem. Interviews were conducted with a representative group of students to understand the underlying causes of their provided designs. We used qualitative research methods to gain refined insights regarding the students’ decision making during the design process. To analyze the gained data, we used content analysis tools. Contribution: The case study presented in this paper will help the teacher to stress the merits and limitations of various parallel architectures and confront students with the consequences of their solutions via performances’ benchmark. Findings: Analysis of the student’s solutions to the first stage revealed that the majority of them did not provide a multi-threaded solution ignoring the optimal runtime requirement. At the second stage, seven various architectures were provided differing in the number of involved threads, the data structures used, and the synchronization mechanism employed. The majority of the solutions were sub-optimal and only a few students provided an optimal one. Recommendations for Practitioners: We recommend conducting class discussions that will follow a task similar to the one used in this study. Recommendation for Researchers: To be able to generalize the received results this research should be repeated with larger study participant groups from various academic institutions. Impact on Society: Understanding the difficulties of novice programmers may lead to quality software systems. Future Research: To be able to generalize the received results this research should be repeated with larger study participant groups from various academic institutions.

Aim/Purpose: In this paper, we present our experience in design and delivery of a graduate Information Systems Management (ISM) course in an online MBA program. Also presented are a detailed examination of the design and delivery of the online course, survey results of students’ perceptions and backgrounds, course evaluation results, best practices and lessons learned, and potential changes and future actions. Background: This graduate ISM course needs to not only cover a broad range of dynamic technology and business topics, but also strike a balance between the width and depth of the content. Effective course design and delivery are critical to improved teaching and learning, especially when the course is delivered online. Methodology: We provided a comprehensive review of the related literature to develop guidelines for the design and delivery of our ISM course; we collected survey data to evaluate the students’ backgrounds and their perceptions of the course; we used data analysis and content analysis methods to assess the course evaluation results. Contribution: A review of the related literature indicates that IS researchers and educators have not adequately studied online graduate education. Given the importance of the graduate ISM course in most MBA programs, and the lack of attention from the IS community, it is critical to address this gap in the research. We believe we have done so with this paper. Findings: The paper’s major findings are embedded in a detailed examination of the design and delivery of the online course, survey results of students’ perceptions and backgrounds, course evaluation results, best practices and lessons learned, and potential changes and future actions. Recommendations for Practitioners: Even though our experience may not be fully applicable to other institutions, we hope our IS colleagues can learn from the design and delivery of this online course, as well as our best practices and lessons learned to improve the teaching and learning effectiveness in IS online graduate education, in general. Furthermore, we provide instructors with an actionable framework onto which they can map their current course offering, and compare their current pedagogical offering to literature driven best practices for ISM courses, in particular. Recommendation for Researchers: It is our hope that the design and delivery of this online course, and our best practices and lessons learned can inspire our IS colleagues to search for innovative ways to improve the teaching and learning effectiveness in IS online graduate education. In addition, we distill a literature driven framework for ISM courses design and delivery that can help researchers frame their pedagogical research questions. Impact on Society: The online course in this study prepares students for more efficiently and effectively delivering IT systems in organizations. Many MBA students work for non-profits and other socially-focused organizations and are able to use the skills learned in the course for the betterment of society. Future Research: We will continue to monitor the impact of the changes on student learning effectiveness and attempt to identify additional innovative ways to improve the design and delivery of this online ISM course.

Aim/Purpose: This study seeks to understand the various ways information systems (IS) students experience introductory programming to inform IS educators on effective pedagogical approaches to teaching programming. Background: Many students who choose to major in information systems (IS), enter university with little or no experience of learning programming. Few studies have dealt with students’ learning to program in the business faculty, who do not necessarily have the computer science goal of programming. It has been shown that undergraduate IS students struggle with programming. Methodology: The qualitative approach was used in this study to determine students’ notions of learning to program and to determine their cognitive processes while learning to program in higher education. A cohort of 47 students, who were majoring in Information Systems within the Bachelor of Commerce degree programme were part of the study. Reflective journals were used to allow students to record their experiences and to study in-depth their insights and experiences of learning to program during the course. Using phenomenographic methods, categories of description that uniquely characterises the various ways IS students experience learning to program were determined. Contribution: This paper provides educators with empirical evidence on IS students’ experiences of learning to program, which play a crucial role in informing IS educators on how they can lend support and modify their pedagogical approach to teach programming to students who do not necessarily need to have the computer science goal of programming. This study contributes additional evidence that suggests more categories of description for IS students within a business degree. It provides valuable pedagogical insights for IS educators, thus contributing to the body of knowledge Findings: The findings of this study reveal six ways in which IS students’ experience the phenomenon, learning to program. These ways, referred to categories of description, formed an outcome space. Recommendations for Practitioners: Use the experiences of students identified in this study to determine approach to teaching and tasks or assessments assigned Recommendation for Researchers: Using phenomenographic methods researchers in IS or IT may determine pedagogical content knowledge in teaching specific aspects of IT or IS. Impact on Society: More business students would be able to program and improve their logical thinking and coding skills. Future Research: Implement the recommendations for practice and evaluate the students’ performance.

Aim/Purpose: The purpose of this paper is to develop and evaluate a debiasing-based approach to assessing the learning materials in problem-based learning (PBL) environments. Background: Research in cognitive debiasing suggests nine debiasing strategies improve decision-making. Given the large number of decisions made in semester-long, problem-based learning projects, multiple tools and techniques help students make decisions. However, instructors may struggle to identify the specific tools or techniques that could be modified to best improve students’ decision-making in the project. Furthermore, a structured approach for identifying these modifications is lacking. Such an approach would match the debiasing strategies with the tools and techniques. Methodology: This debiasing framework for the PBL environment is developed through a study of debiasing literature and applied within an e-commerce course using the Model for Improvement, continuous improvement process, as an illustrative case to show its potential. In addition, a survey of the students, archival information, and participant observation provided feedback on the debiasing framework and its ability to assess the tools and techniques within the PBL environment. Contribution: This paper demonstrates how debiasing theory can be used within a continuous improvement process for PBL courses. By focusing on a cognitive debiasing-based approach, this debiasing framework helps instructors 1) identify what tools and techniques to change in an PBL environment, and 2) assess which tools and techniques failed to debias the students adequately, providing potential changes for future cycles. Findings: Using the debiasing framework in an e-commerce course with significant PBL elements provides evidence that this framework can be used within IS courses and more broadly. In this particular case, the change identified in a prior cycle proved effective and additional issues were identified for improvement. Recommendations for Practitioners: With the growing usage of semester-long PBL projects in business schools, instructors need to ensure that their design of the projects incorporates techniques that improve student learning and decision making. This approach provides a means for assessing the quality of that design. Recommendation for Researchers: This study uses debiasing theory to improve course techniques. Researchers interested in assessment, course improvement, and program improvement should incorporate debiasing theory within PBL environments or other types of decision-making scenarios. Impact on Society: Increased awareness of cognitive biases can help instructors, students, and professionals make better decisions and recommendations. By developing a framework for evaluating cognitive debiasing strategies, we help instructors improve projects that prepare students for complex and multifaceted real-world projects. Future Research: The approach could be applied to multiple contexts, within other courses, and more widely within information systems to extend this research. The framework might also be refined to make it more concise, integrated with assessment, or usable in more contexts.

Aim/Purpose: This paper focuses on designing and implementing the rubric for objective JAVA programming assessments. An unsupervised learning approach was used to group learners based on their performance in the results obtained from the rubric, reflecting their learning ability. Background: Students' learning outcomes have been evaluated subjectively using a rubric for years. Subjective assessments are simple to construct yet inconsistent and biased to evaluate. Objective assessments are stable, reliable, and easy to conduct. However, they usually lack rubrics. Methodology: In this study, a Top-Down assessment approach is followed, i.e., a rubric focused on the learning outcome of the subject is designed, and the proficiency of learners is judged by their performance in conducting the task given. A JAVA rubric is proposed based on the learning outcomes like syntactical, logical, conceptual, and advanced JAVA skills. A JAVA objective quiz (with multiple correct options) is prepared based on the rubric criteria, comprising five questions per criterion. The examination was conducted for 209 students (100 from the MCA course and 109 from B.Tech. course). The suggested rubric was used to compute the results. K-means clustering was applied to the results to classify the students according to their learning preferences and abilities. Contribution: This work contributes to the field of rubric designing by creating an objective programming assessment and analyzing the learners’ performance using machine learning techniques. It also facilitates a reliable feedback approach offering various possibilities in student learning analytics. Findings: The designed rubric, partial scoring, and cluster analysis of the results help us to provide individual feedback and also, group the students based on their learning skills. Like on average, learners are good at remembering the syntax and concepts, mediocre in logical and critical thinking, and need more practice in code optimization and designing applications. Recommendations for Practitioners: The practical implications of this work include rubric designing for objective assessments and building an informative feedback process. Faculty can use this approach as an alternative assessment measure. They are the strong pillars of e-assessments and virtual learning platforms. Recommendation for Researchers: This research presents a novel approach to rubric-based objective assessments. Thus, it provides a fresh perspective to the researchers promising enough opportunities in the current era of digital education. Impact on Society: In order to accomplish the shared objective of reflective learning, the grading rubric and its accompanying analysis can be utilized by both instructors and students. As an instructional assessment tool, the rubric helps instructors to align their pedagogies with the students’ learning levels and assists students in updating their learning paths based on the informative topic-wise scores generated with the help of the rubric. Future Research: The designed rubric in this study can be extended to other programming languages and subjects. Further, an adaptable weighted rubric can be created to execute a flexible and reflective learning process. In addition, outcome-based learning can be achieved by measuring and analyzing student improvements after rubric evaluation.

Aim/Purpose: To encourage students’ engagement in peer assessments and provide students with better-quality feedback, this paper describes a technique for author-reviewer matching in peer assessment systems – a Balanced Allocation algorithm. Background: Peer assessment concerns evaluating the work of colleagues and providing feedback on their work. This process is widely applied as a learning method to involve students in the progress of their learning. However, as students have different ability levels, the efficacy of the peer feedback differs from case to case. Thus, peer assessment may not provide satisfactory results for students. In order to mitigate this issue, this paper explains and evaluates an algorithm that matches the author to a set of reviewers. The technique matches authors and reviewers based on how difficult the authors perceived the assignment to be, and the algorithm then matches the selected author to a group of reviewers who may meet the author’s needs in regard to the selected assignment. Methodology: This study used the Multiple Criteria Decision-Making methodology (MCDM) to determine a set of reviewers from among the many available options. The weighted sum method was used because the data that have been collected in user profiles are expressed in the same unit. This study produced an experimental result, examining the algorithm with a real collected dataset and mock-up dataset. In total, there were 240 students in the real dataset, and it contained self-assessment scores, peer scores, and instructor scores for the same assignment. The mock-up dataset created 1000 records for self-assessment scores. The algorithm was evaluated using focus group discussions with 29 programming students and interviews with seven programming instructors. Contribution: This paper contributes to the field in the following two ways. First, an algorithm using a MCDM methodology was proposed to match authors and reviewers in order to facilitate the peer assessment process. In addition, the algorithm used self-assessment as an initial data source to match users, rather than randomly creating reviewer – author pairs. Findings: The findings show the accurate results of the algorithm in matching three reviewers for each author. Furthermore, the algorithm was evaluated based on students’ and instructors’ perspectives. The results are very promising, as they depict a high level of satisfaction for the Balanced Allocation algorithm. Recommendations for Practitioners: We recommend instructors to consider using the Balanced Allocation algorithm to match students in peer assessments, and consequently to benefit from personalizing peer assessment based on students' needs. Recommendation for Researchers: Several MCDM methods could be expanded upon, such as the analytic hierarchy process (AHP) if different attributes are collected, or the artificial neural network (ANN) if fuzzy data is available in the user profile. Each method is suitable for special cases depending on the data available for decision-making. Impact on Society: Suitable pairing in peer assessment would increase the credibility of the peer assessment process and encourage students’ engagement in peer assessments. Future Research: The Balanced Allocation algorithm could be applied using a single group, and a peer assessment with random matching with another group may also be conducted, followed by performing a t-test to determine the impact of matching on students’ performances in the peer assessment activity.

Aim/Purpose: This study seeks to present a learning model of discrete mathematics elements, elucidate the content of teaching, and validate the effectiveness of this learning in a digital education context. Background: Teaching discrete mathematics in the realm of digital education poses challenges, particularly in crafting the optimal model, content, tools, and methods tailored for aspiring computer science teachers. The study draws from both a comprehensive review of relevant literature and the synthesis of the authors’ pedagogical experiences. Methodology: The research utilized a system-activity approach and aligned with the State Educational Standard. It further integrated the theory of continuous education as its psychological and pedagogical foundation. Contribution: A unique model for instructing discrete mathematics elements to future computer science educators has been proposed. This model is underpinned by informative, technological, and personal competencies, intertwined with the mathematical bedrock of computer science. Findings: The study revealed the importance of holistic teaching of discrete mathematics elements for computer science teacher aspirants in line with the Informatics educational programs. An elective course, “Elements of Discrete Mathematics in Computer Science”, comprising three modules, was outlined. Practical examples spotlighting elements of mathematical logic and graph theory of discrete mathematics in programming and computer science were showcased. Recommendations for Practitioners: Future computer science educators should deeply integrate discrete mathematics elements in their teaching methodologies, especially when aligning with professional disciplines of the Informatics educational program. Recommendation for Researchers: Further exploration is recommended on the seamless integration of discrete mathematics elements in diverse computer science curricula, optimizing for varied learning outcomes and student profiles. Impact on Society: Enhancing the quality of teaching discrete mathematics to future computer science teachers can lead to better-educated professionals, driving advancements in the tech industry and contributing to societal progress. Future Research: There is scope to explore the wider applications of the discrete mathematics elements model in varied computer science sub-disciplines, and its adaptability across different educational frameworks.

Aim/Purpose: The study aims to supplement existing knowledge of information systems by presenting empirical data on the factors influencing the intentions of doctoral students to learn through online platforms. Background: E-learning platforms have become popular among students and professionals over the past decade. However, the intentions of the doctoral students are not yet known. They are an important source of knowledge production in academics by way of teaching and research. Methodology: The researchers collected data from universities in the Delhi National Capital Region (NCR) using a survey method from doctoral students using a convenience sampling method. The model studied was the Technology Readiness and Acceptance Model (TRAM), an integration of the Technology Readiness Index (TRI) and Technology Acceptance Model (TAM). Contribution: TRAM provides empirical evidence that it positively predicts behavioral intentions to learn from online platforms. Hence, the study validated the model among doctoral students from the perspective of a developing nation. Findings: The model variables predicted 49% of the variance in doctoral students’ intent. The TRAM model identified motivating constructs such as optimism and innovativeness as influencing TAM predictors. Finally, doctoral students have positive opinions about the usefulness and ease of use of online learning platforms. Recommendations for Practitioners: Academic leaders motivate scholars to use online platforms, and application developers to incorporate features that facilitate ease of use. Recommendation for Researchers: Researchers can explore the applicability of TRAM in other developing countries and examine the role of cultural and social factors in the intent to adopt online learning. Future Research: The influence of demographic variables on intentions can lead to additional insights.

Aim/Purpose: The study examined how the developed mobile courseware can be used as instructional material to improve senior high school statistics and probability learning, particularly during distance learning caused by the COVID-19 pandemic. The study also aims to assess the gamified mobile courseware’s engagement, functionality, aesthetics, and information quality using the Mobile App Rating Scale (MARS) and a researcher-made Gamified Mobile Courseware Assessment Tool (GMCET). Background: The need to investigate the effectiveness of incorporating game-based elements into mathematics courses through innovative instructional materials inspired the study. The COVID-19 pandemic has made distance learning a necessity, and gamified mobile courseware is a potential solution to improve learning outcomes and engagement in mathematics courses. Methodology: The study employed a descriptive-evaluative method with quantitative and qualitative data to achieve its objectives. Five IT practitioners assessed the developed courseware using the MARS regarding engagement, functionality, aesthetics, and information. A researcher-made GMCET was also used to evaluate the app’s content quality, learning objectives, content presentation, learning assessment, and usability. Five math experts and 12 math teachers rated the app using the GMCET. The study used weighted mean to analyze the quantitative data and content analysis for the qualitative data. Contribution: The study provides insights into the strengths and weaknesses of gamified mobile courseware from the perspective of IT practitioners, math experts, and math teachers. The study’s findings can inform improvements in future iterations of courseware, and the study provides a valuable guide for practitioners looking to develop gamified mobile courseware for mathematics courses. Findings: The quantitative results based on the weighted mean indicate that the IT practitioners had a moderately positive perception of the developed courseware across all categories. At the same time, the math teachers and math experts showed highly positive perceptions of the gamified mobile courseware in Statistics and Probability, rating it highly across all categories. The qualitative data analysis through content analysis highlights the need for improving the user interface, usability, user experience design, user control, flexibility in interaction, data quality, reliability, and user privacy of the developed app. Recommendations for Practitioners: Practitioners can use the study’s findings to improve the design of gamified mobile courseware for mathematics courses and other content areas. The study recommends that practitioners focus on improving the user interface, usability, user experience design, user control, flexibility in interaction, data quality, reliability, and user privacy of gamified mobile courseware. Recommendation for Researchers: Future research can build on this study’s findings by exploring the use of gamified mobile courseware in other mathematical courses and other subject areas. Further research can also examine how gamified mobile courseware can improve learning outcomes for students with different learning needs. Impact on Society: The study’s findings could improve the effectiveness of gamified mobile courseware in enhancing student learning outcomes in mathematics courses. This can lead to better student performance, improved engagement, and increased interest in mathematics courses, positively impacting society. Future Research: Future research can explore using gamified mobile courseware in other mathematics courses and other subject areas. Additionally, future studies can examine how gamified mobile courseware can improve learning outcomes for students with different learning needs. Further research can also investigate the impact of gamified mobile courseware on student motivation, interest, and performance in mathematics courses.

Aim/Purpose: The emergence of massive open online courses (MOOCs) has fostered the creation of co-located learning communities; however, there is limited research on the types of interactions unfolding in these spaces. Background: This study explores Peer 2 Peer University’s Learning Circles, a project that allows individuals to take MOOCs together at the library. I investigated the patterns that emerged from the interactions between facilitators, learners, course materials, and digital media in the pilot round of these Learning Circles. Methodology: This study employs an ethnography of hybrid spaces (online/offline participant observations, in-depth interviews, and artifact collection) of face-to-face study groups taking place at library branches in a Midwest metropolitan area. Data analysis employs the constant comparison method. Contribution: Interactions taking place in the Learning Circles increased individuals’ agency as learners and subverted the MOOC model through processes of technological appropriation. Findings: The findings reveal that interactions within Learning Circles created a dynamic negotiation of roles, produced tension points, enabled a distributed model of knowledge, and structured study routines. The pilot round of Learning Circles attracted diverse participants beyond the typical digitally literate MOOC student. Many of them had no previous experience taking online courses and, in some cases, no Internet connection at home. This paper argues that Learning Circles favored the appropriation of artifacts (technologies) and increased participants’ agency as learners in the Internet age. Recommendations for Practitioners: Practitioners can use the Learning Circles model to benefit disenfranchised individuals by providing them with access to materials resources and a network of peers that can help increase their agency as learners. Recommendation for Researchers: This study suggests that it is fundamental to pay attention to learning initiatives that are unfolding outside the scope of traditional and formal education. Impact on Society: Open educational resources and public libraries are opening new pathways for learning beyond traditional higher education institutions. Future Research: Future research can explore how the learning circles are adapted in cultural contexts outside the United States.

Aim/Purpose: This study presents some activities that integrate computational thinking (CT) into mathematics lessons utilizing GeoGebra to promote constructionist learning. Background: CT activities in the Indonesian curriculum are dominated by worked examples with less plugged-mode activities that might hinder students from acquiring CT skills. Therefore, we developed mathematics and CT (math+CT) lessons to promote students’ constructionist key behaviors while learning. Methodology: The researchers utilized an educational design research (EDR) to guide the lesson’s development. The lesson featured 11 applets and 22 short questions developed in GeoGebra. To improve the lesson, it was sent to eight mathematics teachers and an expert in educational technology for feedback, and the lesson was improved accordingly. The improved lessons were then piloted with 17 students, during which the collaborating mathematics teachers taught the lessons. Data were collected through the students’ work on GeoGebra, screen recording when they approached the activities, and interviews. We used content analysis to analyze the qualitative data and presented descriptive statistics to quantitative data. Contribution: This study provided an example and insight into how CT can be enhanced in mathematics lessons in a constructionist manner. Findings: Students were active in learning mathematics and CT, especially when they were engaged in programming and debugging tasks. Recommendations for Practitioners: Educators are recommended to use familiar mathematics software such as GeoGebra to support students’ CT skills while learning mathematics. Additionally, our applets are better run on big-screen devices to optimize students’ CT programming and debugging skills. Moreover, it is recommended that students work collaboratively to benefit from peer feedback and discussion. Recommendation for Researchers: Collaboration with teachers will help researchers better understand the situation in the classroom and how the students will respond to the activities. Additionally, it is important to provide more time for students to get familiar with GeoGebra and start with fewer errors to debug. Future Research: Further research can explore more mathematics topics when integrating CT utilizing GeoGebra or other mathematics software or implement the lessons with a larger classroom size to provide a more generalizable result and deeper understanding.

Aim/Purpose: The aim of the study is to test whether the perception of self-regulated learning during text reading in online teacher education is improved by using a digital tool for the use of metacognitive strategies for planning, monitoring, and self-assessment. Background: The use of self-regulated learning is important in reading skills, and for students to develop self-regulated learning, their teachers must master it. Therefore, teaching strategies for self-regulated learning in teacher education is essential. Methodology: The sample size was 252 participants with the tool used by 42% or the participants. A quasi-experimental design was used in a pre-post study. ARATEX-R, a text-based scale, was used to evaluate self-regulated learning. The 5-point Likert scale includes the evaluation of five dimensions: planning strategies, cognition management, motivation management, comprehension assessment and context management. A Generalized Linear Model was used to analyse the results. Contribution: Using the tool to self-regulate learning has led to an improvement during text reading, especially in the dimensions of motivation management, planning management and comprehension assessment, key dimensions for text comprehension and learning. Findings: Participants who use the app perceive greater improvement, especially in the dimensions of motivation management (22,3%), planning management (19.9%) and comprehension assessment (24,6%), which are fundamental dimensions for self-regulation in text reading. Recommendations for Practitioners: This tool should be included in teacher training to enable reflection during the reading of texts, because it helps to improve three key types of strategies in self-regulation: (1) planning through planning management, (2) monitoring through motivation management and comprehension assessment, and (3) self-assessment through comprehension assessment. Recommendation for Researchers: The success of the tool suggests further study for its application in other use cases: other student profiles in higher education, other teaching modalities, and other educational stages. These studies will help to identify adaptations that will extend the tool’s use in education. Impact on Society: The use of Metadig facilitates reflection during the reading of texts in order to improve comprehension and thus self-regulate the learning of content. This reflection is crucial for students’ knowledge construction. Future Research: Future research will focus on enhancing the digital tool by adding features to support the development of cognition and context management. It will also focus on how on adapting the tool to help other types of learners.

Aim/Purpose: To conduct a needs assessment and subsequently create micro-storytelling media aimed at enhancing the Digital Intelligence Quotient (DQ) skills of young individuals. Background: In today's digital society, DQ has emerged as a vital skill that elevates individuals in all aspects of life, from daily living to education. To empower Thai youth, this study seeks to innovate DQ content by adapting it into a digital format known as micro-storytelling. This unique approach combines the art of storytelling with digital elements, creating engaging and effective micro-learning media Methodology: The methodology comprises three phases: 1) assessing the need for digital micro-storytelling development; 2) developing digital micro-storytelling; and 3) evaluating the DQ skills among young individuals. The sample group consisted of 55 higher education learners for needs assessment and 30 learners in the experiment group. Data analysis involves PNI modified, mean, and standard deviation. Contribution: This research contributes by addressing the urgent need for DQ skills in the digital era and by providing a practical solution in the form of digital micro-storytelling, tailored to the preferences and needs of Thai youth. It serves as a valuable resource for educators and policymakers seeking to empower young learners with essential digital competencies. Findings: The findings demonstrate three significant outcomes: 1) The learners wanted to organize their own learning experience with self-paced learning in a digital landscape, and they preferred digital media in the form of video. They were most interested in developing DQ to enhance their understanding of digital safety, digital security, and digital literacy; 2) according to a consensus of experts, digital micro-storytelling has the greatest degree of quality in terms of its development, content, and utilization, with an overall average of 4.86; and 3) the overall findings of the assessment of DQ skills indicate a favorable level of proficiency. Recommendations for Practitioners: Align materials with micro-learning principles, keeping content concise for effective knowledge retention. Empower students to personalize their digital learning and promote self-paced exploration based on their interests. Recommendation for Researchers: Researchers should continuously assess and update digital learning materials to align with the evolving digital landscape and the changing needs of students and investigate the long-term effects of DQ improvement, especially in terms of online safety and digital literacy in students' future lives and careers. Impact on Society: This study's impact on society is centered around fostering a DQ, promoting innovative educational approaches, and elevating Thai youth with essential digital skills. It contributes to a safer, more informed, and digitally literate generation prepared for the challenges of the digital era. Future Research: Undertake comparative studies to analyze the effectiveness of different digital learning formats and methodologies. Comparing micro-storytelling with other approaches can help identify the most efficient and engaging methods for enhancing DQ.

Aim/Purpose: This exploratory qualitative case study examines the perceptions of high-school learners of English regarding a pedagogical intervention involving progressive reduction of captions (full, sentence-level, keyword captions, and no-captions) in enhancing language learning. Background: Recognizing the limitations of caption usage in fostering independent listening comprehension in non-captioned environments, this research builds upon and extends the foundational work of Vanderplank (2016), who highlighted the necessity of a comprehensive blend of tasks, strategies, focused viewing, and the need to actively engage language learners in watching captioned materials. Methodology: Using a qualitative research design, the participants were exposed to authentic video texts in a five-week listening course. Participants completed an entry survey, and upon interaction with each captioning type, they wrote individual reflections and participated in focus group sessions. This methodological approach allowed for an in-depth exploration of learners’ experiences across different captioning scenarios, providing a nuanced understanding of the pedagogical intervention’s impact on their perceived language development process. Contribution: By bridging the research-practice gap, our study offers valuable insights into designing pedagogical interventions that reduce caption dependence, thereby preparing language learners for success in real-world, caption-free listening scenarios. Findings: Our findings show that learners not only appreciate the varied captioning approaches for their role in supporting text comprehension, vocabulary acquisition, pronunciation, and on-task focus but also for facilitating the integration of new linguistic knowledge with existing background knowledge. Crucially, our study uncovers a positive reception towards the gradual shift from fully captioned to uncaptioned materials, highlighting a stepwise reduction of caption dependence as instrumental in boosting learners’ confidence and sense of achievement in mastering L2 listening skills. Recommendations for Practitioners: The implications of our findings are threefold: addressing input selection, task design orchestration, and reflective practices. We advocate for a deliberate selection of input that resonates with learners’ interests and contextual realities alongside task designs that progressively reduce caption reliance and encourage active learner engagement and collaborative learning opportunities. Furthermore, our study underscores the importance of reflective practices in enabling learners to articulate their learning preferences and strategies, thereby fostering a more personalized and effective language learning experience. Recommendation for Researchers: Listening comprehension is a complex process that can be clearly influenced by the input, the task, and/or the learner characteristics. Comparative studies may struggle to control and account for all these variables, making it challenging to attribute observed differences solely to caption reduction. Impact on Society: This research responds to the call for innovative teaching practices in language education. It sets the stage for future inquiries into the nuanced dynamics of caption usage in language learning, advocating for a more learner-centered and adaptive approach. Future Research: Longitudinal quantitative studies that measure comprehension as captions support is gradually reduced (full, partial, and keyword) are strongly needed. Other studies could examine a range of individual differences (working memory capacity, age, levels of engagement, and language background) when reducing caption support. Future research could also examine captions with students with learning difficulties and/or disabilities.

Forensic document forgery investigations have elevated the need for source identification for printed documents during the past few years. It is necessary to create a reliable and acceptable safety testing instrument to determine the credibility of printed materials. The proposed system in this study uses a neural network to detect the original printer used in forensic document forgery investigations. The study uses a deep neural network method, which relies on the quality, texture, and accuracy of images printed by various models of Canon and HP printers. The datasets were trained and tested to predict the accuracy using logical function, with the goal of creating a reliable and acceptable safety testing instrument for determining the credibility of printed materials. The technique classified the model with 95.1% accuracy. The proposed method for identifying the source of the printer is a non-destructive technique.

The use of electronic means of a public official in carrying out their duties may lead to an instance wherein the person discloses confidential information, which can significantly impact their obligations. After verifying this act as part of electronic misconduct, disciplinary action is enforced upon the concerned party to rectify and ensure proper functioning in delivering public services without any disturbance or infringement. The study presents several significant findings regarding the absence of comparative regulations concerning electronic violations and their judicial evidence. It provides recommendations such as modifying legislative frameworks to enhance public utility disciplinary systems and incorporating rules for electric violations. The fundamental focus revolves around assessing, verifying, and punishing digital misconduct by management or regulatory bodies. Additionally, this research employs descriptive-analytical methods comparing the Jordanian Law with its Egyptian counterpart in exploring these issues.

The present study attempts to find out the determinants of FinTech adoption for financial inclusion by a microfinance institution in India. The factors such as efficiency, consistency, convenience, reliability are taken as predictors of organisational attitude. Similarly, organisational attitude, ease of use, and perceived benefits are considered as antecedents of organisational adoption intention of FinTech in microfinance institutions of India. The purposive sampling technique was used to get a filled survey instrument by target samples. The results indicate that convenience and consistency in the use of FinTech applications build a favourable attitude to adopt it. Furthermore, perceived benefits are the most important antecedents of the adoption intention of FinTech in the microfinance institution in India. Additionally, the reliability of the application has a positive but insignificant impact on organisational attitude to adopt FinTech. The implications of the present study are discussed.

Quality of work life (QWL) is a generic term that includes an employee's feeling about various aspects of their work including the compensation and rewards, job security, interpersonal relations and the intrinsic meaning of being satisfied in their workplace. This research paper was documented with an intention to understand the influence of the QWL on the productivity of employees working in the banking arena. The study examined the most clout able factors that contributed to the quality of work-life of employees and its correlation on their productivity. A multi-stage sampling method was used to draw a sizeable sample from ten major banks situated in the Karnataka state of India. A total of 756 personnel spread across various branches belonging to rural, semi-urban and urban were covered. The study was validated further by testing various hypotheses drawn based on a review of the literature. The study empirically identified eight major attributes that influence the QWL of bankers. The relationship between QWL and productivity was investigated with notable results using SEM approach.

Badminton, as a fast and highly technical sport, requires high accuracy in identifying athletes' swing movements. Accurately identifying different swing movements is of great significance for technical analysis, coach guidance, and game evaluation. To improve the recognition accuracy of badminton players' swing movements, this text is based on an improved dense trajectory algorithm to improve the accuracy of recognising badminton players' swing movements. The features are efficiently extracted and encoded. The results on the KTH, UCF Sports, and Hollywood2 datasets demonstrated that the improved algorithm achieved recognition accuracy of 94.2%, 88.2%, and 58.3%, respectively. Compared to traditional methods, the innovation of research lies in optimised feature extraction methods, efficient algorithm design, and accurate action recognition. These results provide new ideas for the research and application of badminton swing motion recognition.

In the competitive landscape of globalised markets, businesses must prioritise cost reduction for sustained competitiveness. This study delves into the dynamic facility layout problem (DFLP) within a cable production company in Kerala, emphasising adaptability to changing production demands. Addressing material handling costs and rearrangement expenses, the research evaluates the efficacy of the current static layout and explores the benefits of transitioning to a dynamic layout. The case study reveals potential cost savings through the strategic restructuring of machine arrangements. The innovative machine learning-based genetic algorithm (ML-GA) integrates machine learning algorithms, genetic algorithms, and a local search method, offering a cutting-edge solution to dynamic facility layout challenges. By considering demand variability and relocation costs, the study provides insights for informed decision-making, emphasising the significance of material flow patterns. This research contributes to enhancing efficiency and profitability, providing practical implications for businesses navigating the complexities of modern manufacturing.

In this paper, we study and provide algorithms for source-provenance of answers to extended SPARQL queries. Extended SPARQL queries are an extension of SPARQL 1.1 queries which support not only a single dataset but multiple datasets, each in a particular context. For example, normal subqueries, aggregate subqueries, (NOT) EXISTS filter subqueries may (optionally) have their own dataset. Additionally, GRAPH patterns can query multiple RDF graphs from the local FROM NAMED dataset and not just one. For monotonic queries, the source why provenance sets that we derive for an answer mapping are each the minimal set of sources appearing in the query that if we consider as they are while the rest of the sources are considered empty, we derive the same answer mapping. We show that this property does not hold for non-monotonic queries. Among others, knowing source why provenance is of critical importance for judging confidence on the answer, allow information quality assessment, accountability, as well as understanding the temporal and spatial status of information.

In the construction sector, moulding machines are crucial in producing concrete products, yet changing their mould can pose challenges for some businesses. This paper presents a case study aimed at reducing the setup time of HESS RH 600 moulding machine. Four alternatives are proposed and evaluated to achieve this goal. The first alternative involves converting internal to external activities, while the subsequent alternatives aim to improve the basic solution. These include building a canopy near the machine (alternative 2), installing an air reservoir (alternative 3), and a comprehensive approach involving building the canopy, installing the air reservoir, and adding a new forklift to facilitate the machine setup process (alternative 4). The analytic hierarchy process (AHP) heuristic method is used to select the best alternative solution based on prespecified criteria. It is found that the application of the single-minute exchange of die (SMED) solution without any further improvement is the most favourable.

Though there have been many approaches to dealing with social problems in recent years, the concepts of social value have yet to be discussed thoroughly. Upon examining these concepts in existing studies and testing them with two case studies, the article shows that there is the possibility that a group's shared wants may not be widely recognised as a social problem, and targeting these unserved populations is a precondition for solving social issues. It is essential to identify hidden social problems by understanding what is still left, the number of people sharing the same want, the severity of the unmet want, and the possible resources for solution generation. Social value in its narrower definition means meeting the satisfaction of the group sharing the same want, while in its broader definition, it means meeting the satisfaction of wider society. Finding workable solutions involves not only the group of people sharing the same want but also others who do not have the same want but who do recognise the importance of acknowledging the want of the subgroup.

Aiming at the problems of long evaluation time and poor evaluation accuracy of existing evaluation methods, an improved decision tree-based evaluation method for the effectiveness of college online course teaching reform is proposed. Firstly, the teaching mode of college online course is analysed, and an evaluation system is constructed to ensure the applicability of the evaluation method. Secondly, AHP entropy weight method is used to calculate the weights of evaluation indicators to ensure the accuracy and authority of evaluation results. Finally, the evaluation model based on decision tree algorithm is constructed and improved by fuzzy neural network to further optimise the evaluation results. The parameters of fuzzy neural network are adjusted and gradient descent method is used to optimise the evaluation results, so as to effectively evaluate the effect of college online course teaching reform. Through experiments, the evaluation time of the method is less than 5 ms, and the evaluation accuracy is more than 92.5%, which shows that the method is efficient and accurate, and provides an effective evaluation means for the teaching reform of online courses in colleges and universities.

In order to improve recommendation coverage, a personalised recommendation method for English online learning resources based on improved collaborative filtering algorithm is studied to enhance the comprehensiveness of personalised recommendation for learning resources. Use matrix decomposition to decompose the user English online learning resource rating matrix. Cluster low dimensional English online learning resources by improving the K-means clustering algorithm. Based on the clustering results, calculate the backfill value of English online learning resources and backfill the information matrix of low dimensional English online learning resources. Using an improved collaborative filtering algorithm to calculate the predicted score of learning resources, personalised recommendation of English online learning resources for users based on the predicted score. Experimental results have shown that this method can effectively backfill English online learning resources, and the resource backfilling effect is excellent, and it has a high recommendation coverage rate.

The value and utility of traditional knowledge in conserving and commercialising genetic resources are increasingly becoming apparent due to advances in biotechnology and bioprospecting. However, the absence of an international legally binding instrument within the WIPO system means that traditional knowledge associated with genetic resources is not sufficiently protected like other forms of intellectual property. This means that indigenous peoples and local communities (IPLCs) do not benefit from the commercial exploitation of these resources. The efficacy of domestic tools to protect traditional knowledge and in balancing the rights of IPLCs and intellectual property rights (IPRs) is still debated. This paper employs a doctrinal research methodology based on desktop research of international and regional law instruments and the Constitution of the Republic of South Africa, 1996, to determine the basis for balancing the protection of genetic resources and associated traditional knowledge with competing interests of IPLCs and IPRs in South Africa.

Presently, there are many existing academic studies on the development, protection and operation of intellectual property management (IPM). Therefore, provides a comprehensive econometric analysis in order to provide scholars, with a clearer understanding of the evolution and development of IP management research during 2000 to 2022. The study is aiming to help scholars to better discern the expanding IPM research field from a multidimensional perspective. The database used for this analysis is the Web of Science Core Collection database. After retrieval through keywords and using a variety of tools such as CiteSpace, VOSviewer, Bibliometrix and HistCite, 1033 documents were refined to conduct the econometric analysis, and produce graphs. The findings indicate that the US is a highly active country/region in the field IP management research, and its expanding IP management research is branching out into other disciplines. The study also presents the future directions and possible challenges for IPM in technology management.

Intellectual property rights face new obstacles and possibilities as a result of the emergence of the Metaverse, a simulation of the actual world. This paper explores the current status of intellectual property rights in the Metaverse and examines the challenges and opportunities for enforcement. The article describes virtual assets and investigates their copyright and trademark protection. It also examines the protection of user-generated content in the Metaverse and the potential liability for copyright infringement. The article concludes with a consideration of the technological and jurisdictional obstacles to enforcing intellectual property rights in the Metaverse, as well as possible solutions for stakeholders. This paper will appeal to lawyers, policymakers, developers of virtual assets, platform owners, and anyone interested in the convergence of technology and intellectual property rights.

In view of the problems of low accuracy, long time consuming and low efficiency of the existing engineering investment risk assessment method; this paper puts forward the investment risk assessment method of power grid construction project based on grey correlation analysis. Firstly, classify the risks of power grid construction project; secondly, determine the primary index and secondary index of investment risk assessment of power grid construction project; then construct the correlation coefficient matrix of power grid project investment risk to calculate the correlation degree and weight of investment risk index; finally, adopt the grey correlation analysis method to construct investment risk assessment function to realise investment risk assessment. The experimental results show that the average accuracy of evaluating the investment risk of power grid construction projects using the method is 95.08%, and the maximum time consuming is 49 s, which proves that the method has high accuracy, short time consuming and high evaluation efficiency.

Because of the problems of low mining precision and slow mining speed in traditional enterprise marketing investment data mining methods, a fast mining method for enterprise marketing investment databased on improved association rules is proposed. First, the enterprise marketing investment data is collected through the crawler framework, and then the collected data is cleaned. Then, the cleaned data features are extracted, and the correlation degree between features is calculated. Finally, according to the calculation results, all data items are used as constraints to reduce the number of frequent itemsets. A pruning strategy is designed in advance. Combined with the constraints, the Apriori algorithm of association rules is improved, and the improved algorithm is used to calculate all frequent itemsets, Obtain fast mining results of enterprise marketing investment data. The experimental results show that the proposed method is fast and accurate in data mining of enterprise marketing investment.

In order to solve the problems of large generalisation error, low recall rate and low retrieval accuracy of customer evaluation information in traditional trust evaluation methods, an evaluation method of customer trust in e-commerce market based on entropy weight analytic hierarchy process was designed. Firstly, build an evaluation index system of customer trust in e-commerce market. Secondly, the customer trust matrix is established, and the index weight is calculated by using the analytic hierarchy process and entropy weight method. Finally, five-scale Likert method is used to analyse the indicator factors and establish a comment set, and the trust evaluation value is obtained by combining the indicator membership. The experiment shows that the maximum generalisation error of this method is only 0.029, the recall rate is 97.5%, and the retrieval accuracy of customer evaluation information is closer to 1.

The EU 'General Data Protection Regulation' (GDPR) marked the most important step towards reforming data privacy regulation in recent years, as it has brought about significant changes in data process in various sectors, ranging from healthcare to banking and beyond. Various concerns have been raised, and as a consequence of these, certain parts of the text of the GDPR itself have already started to become questionable due to rapid technological progress, including, for example, the use of information technology, automatisation processes and advanced algorithms in individual decision-making activities. The road to GDPR compliance by all European Union members may prove to be a long one and it is clear that only time will tell how GDPR matters will evolve and unfold. In this paper, we aim to offer a review of the practical, ethical and constitutional aspects of the new regulation and examine all the controversies that the new technology has given rise to in the course of the regulation's application.