Aim/Purpose: One of the main objectives of higher education institutions is to provide a high-quality education to their students and reduce dropout rates. This can be achieved by predicting students’ academic achievement early using Educational Data Mining (EDM). This study aims to predict students’ final grades and identify honorary students at an early stage. Background: EDM research has emerged as an exciting research area, which can unfold valuable knowledge from educational databases for many purposes, such as identifying the dropouts and students who need special attention and discovering honorary students for allocating scholarships. Methodology: In this work, we have collected 300 undergraduate students’ records from three departments of a Computer and Information Science College at a university located in Saudi Arabia. We compared the performance of six data mining methods in predicting academic achievement. Those methods are C4.5, Simple CART, LADTree, Naïve Bayes, Bayes Net with ADTree, and Random Forest. Contribution: We tested the significance of correlation attribute predictors using four different methods. We found 9 out of 18 proposed features with a significant correlation for predicting students’ academic achievement after their 4th semester. Those features are student GPA during the first four semesters, the number of failed courses during the first four semesters, and the grades of three core courses, i.e., database fundamentals, programming language (1), and computer network fundamentals. Findings: The empirical results show the following: (i) the main features that can predict students’ academic achievement are the student GPA during the first four semesters, the number of failed courses during the first four semesters, and the grades of three core courses; (ii) Naïve Bayes classifier performed better than Tree-based Models in predicting students’ academic achievement in general, however, Random Forest outperformed Naïve Bayes in predicting honorary students; (iii) English language skills do not play an essential role in students’ success at the college of Computer and Information Sciences; and (iv) studying an orientation year does not contribute to students’ success. Recommendations for Practitioners: We would recommend instructors to consider using EDM in predicting students’ academic achievement and benefit from that in customizing students’ learning experience based on their different needs. Recommendation for Researchers: We would highly endorse that researchers apply more EDM studies across various universities and compare between them. For example, future research could investigate the effects of offering tutoring sessions for students who fail core courses in their first semesters, examine the role of language skills in social science programs, and examine the role of the orientation year in other programs. Impact on Society: The prediction of academic performance can help both teachers and students in many ways. It also enables the early discovery of honorary students. Thus, well-deserved opportunities can be offered; for example, scholarships, internships, and workshops. It can also help identify students who require special attention to take an appropriate intervention at the earliest stage possible. Moreover, instructors can be aware of each student’s capability and customize the teaching tasks based on students’ needs. Future Research: For future work, the experiment can be repeated with a larger dataset. It could also be extended with more distinctive attributes to reach more accurate results that are useful for improving the students’ learning outcomes. Moreover, experiments could be done using other data mining algorithms to get a broader approach and more valuable and accurate outputs.

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: The purpose of this research is to determine whether ESL teaching videos as a form of asynchronous online knowledge sharing can act as an aid to ESL learners internalizing knowledge in language acquisition. In this context, internalizing knowledge carries the meaning of being able to remember language, and purposefully and accurately use it context, including appropriacy of language, and aspects of correct pronunciation, intonation, stress patterns and connected speech, these being the elements of teaching and practice that are very often lacking in asynchronous, online, instructional video. Background: Knowledge Management is the field of study, and the practice, of discovering, capturing, sharing, and applying knowledge, typically with a view to translating individuals’ knowledge into organizational knowledge. In the field of education, it is the sharing of instructors’ knowledge for students to be able to learn and usefully apply that knowledge. In recent pandemic times, however, the mode of instruction has, of necessity, transitioned from face-to-face learning to an online environment, transforming the face of education as we know it. While this mode of instruction and knowledge sharing has many advantages for the online learner, in both synchronous and asynchronous learning environments, it presents certain challenges for language learners due to the absence of interaction and corrective feedback that needs to take place for learners of English as a Second Language (ESL) to master language acquisition. Unlike other subjects where the learner has recourse to online resources to reinforce learning through referencing external information, such as facts, figures, or theories, to be successful in learning a second language, the ESL learner needs to be able to learn to process thought and speech in that language; essentially, they need to learn to think in another language, which takes time and practice. Methodology: The research employs a systematic literature review (SLR) to determine the scope and extent to which the subject is covered by existing research in this field, and the findings thereof. Contribution: Whilst inconclusive in relation to internalizing language through online, asynchronous instructional video, through its exploratory nature, the research contributes towards the body of knowledge in online learning through the drawing together of various studies in the field of learning through asynchronous video through improving video and instructional quality. Findings: The findings of the systematic literature review revealed that there is negligible research in this area, and while information exists on blended and flipped modes of online learning, and ways to improve the quality and delivery of instructional video generally, no prior research on the exclusive use of asynchronous videos as an aid to internalizing English as a second language were found. Recommendations for Practitioners: From this research, it is apparent that there is considerably more that practitioners can do to improve the quality of instructional videos that can help students engage with the learning, from which students stand a much better chance of internalizing the learning. Recommendation for Researchers: For researchers, the absence of existing research is an exciting opportunity to further explore this field. Impact on Society: Online learning is now globally endemic, but it poses specific challenges in the field of second language learning, so the development of instructional videos that can facilitate this represents a clear benefit to all ESL learners in society as a whole. Future Research: Clearly the absence of existing research into whether online asynchronous instructional videos can act as an aid to internalizing the acquisition of English as a second language would indicate that this very specific field is one that merits future research. Indeed, it is one that the author intends to exploit through primary data collection from the production of a series of asynchronous, online, instructional videos.

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: This study explores the subject structure, social networks, research trends, and issues in the domain that have the potential to derive an overview of the development of virtual reality-based learning media in vocational education. Background: Notwithstanding the increasingly growing interest in the application of virtual reality in vocational learning, the existing research literature may still leave out some issues necessary for a comprehensive understanding. This study will point out such areas that need more exploration and a more comprehensive synthesis of the literature by conducting a bibliometric analysis. It will be interesting to keep track of the changing concepts and methodologies applied in the development of VR-based learning media in vocational education research. Methodology: This review was carried out using bibliometric methodology, which can highlight patterns of publication and research activity in this hitherto little studied area. The results of the study have the potential to lead to evidence-based priority in VR development, which will tailor work for vocational contexts and set the compass against the growing worldwide interest in this area. The study provides a descriptive analysis of publications, citations, and keyword data for 100 documents published between the years 2013 and 2022 from the Scopus database, which is conducted to illustrate the trends in the field. Contribution: This study also counts as a contribution to understanding the research hotspots of VR-based learning media in vocational education. Through bibliometric analysis, this study thoroughly summarized the relevant research and literature laying a knowledge foundation for researchers and policy makers. Additionally, this analysis identified knowledge gaps, recent trends, and directions for future research. Findings: The bibliometric analysis revealed the following key findings: 1. A growing publication trajectory, with output increasing from 7 articles in 2013 to 25 articles in 2022. 2. The United States led the contributions, followed by China, and Germany. 3. The most prominent authors are affiliated with American medical institutions. 4. Lecture proceedings include familiar sources that reflect this nascent domain. 5. Citation analysis identified highly influential work and researchers. 6. Keyword analysis exposed technology-oriented topics rather than learning-oriented terms. These findings present an emerging landscape with opportunities to address geographic and pedagogical research gaps. Recommendations for Practitioners: This study will be beneficial for designers and developers of VR-based learning programs because it aligns with the most discussed and influential VR technologies within the literature. Such an alignment of an approach with relevant research trends and focus can indeed be very useful for the effective application and use of VR-based learning media for quality improvements in vocational students' learning. Recommendation for Researchers: In fact, in this bibliometric review of VR integration within vocational classrooms, a future call for focused research is presented, especially on teaching methods, course design, and learning impact. This is a framework that seeks to establish its full potential with effective and integrated use of VR in the various vocational curricula and settings of learners. Impact on Society: From the findings of the bibliometric analysis, it is evident that virtual reality technologies (VR) have significantly led to transformation within educational media. There is no denying that the growing interest and investment in the integration of virtual reality into vocational education has been well manifested in the substantive increase in publications in the last decade. This shows what the innovation driving factor is in the United States. At the same time the rapid contributions from China signal worldwide recognition of the potential of VR to improve technical skills training. This study points the way for more research to bridge critical gaps, specifically how VR tools can be used in vocational high school classrooms. Furthermore, research should be aligned to meet specific needs of vocational learners and even promote international cross-border partnerships, pointing out the potential of virtual reality to be a universally beneficial tool in vocational education. The examination of highly cited articles provides evidence of the potential of VR to be an impactful pedagogical tool in vocational education. The findings suggest that researchers need to move forward looking at the trajectory of VR in vocational education and how promising it is in defining the future for innovative and effective learning methodologies. Future Research: This study is an exceptionally valuable contribution, a true landmark in the field of dynamic development, and one that denotes very meaningful implications for the future course of research in the dynamically developing field of bibliometric analysis of VR-based learning media for vocational education. The increase in the number of publications emanates from growing interests in the application of virtual reality (VR) technologies in vocational education. The high concentration of authorship from the USA, along with the ever increasing contributions from China, spotlights the increasing worldwide recognition of the impact of immersive technologies in the enhancement of training in technical skills. These are emerging trends that call for research to exemplify the diverse views and global teamwork opportunities presented by VR technologies. The study also highlights critical areas that need focused attention in future research endeavors. The fact that the embedding of VR tools into classrooms in vocational high schools has been poorly researched points to the major gap in pedagogical research within authentic educational settings. Therefore, further investigations should evaluate teaching methods in VR, lesson designs, and the impacts of VR in specific vocational trades. This supports the need for learner-centered frameworks that are tailor-made to the needs of vocational learners. This calls for more direct and focused investigations into identified research gaps noting a growing dominance in the field of health-related research with the most cited articles in this field, to integrate virtual reality into additional vocational education contexts. In this way, the gaps present an opportunity for researchers to make significant contributions to the development of interventions responsive to the unique needs of vocational learners; this will contribute to strengthening the evidence base for the worldwide implementation of VR within vocational education systems. This was recommended as the intention of such a bibliometric analysis: supporting the potential of VR as a pedagogical tool in vocational contexts and providing grounding for a strong and focused future research agenda within this burgeoning area of educational technology.

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: The digital ecosystem has contributed to the acceleration of digital and mobile educational tools across institutions worldwide. The research displays educators’ perspectives on web applications on mobile devices that can be used to engage and challenge students while impacting their learning. Background: Explored are elements of technology in education and challenges and successes reported by instructors to shift learning from static to dynamic. Methodology: Insights for this study were gained through questionnaires and focus groups with university educators in the United Arab Emirates. Key questions addressed are (1) challenges/benefits, (2) types of mobile technology applications used by educators, and (3) strategies educators use to support student learning through apps. The research is assisted by focus groups and a sample of 42 completed questionnaires. Contribution: The work contributes to web/mobile strategic considerations in the classroom that can support student learning and outcomes. Findings: The results reported showcase apps that were successfully implemented in classrooms and provide a perspective for today’s learning environment that could be useful for instructors, course developers, or any educational institutions. Recommendations for Practitioners: Academics can integrate suggested tools and explore engagement and positive associations with tools and technologies. Recommendation for Researchers: Researchers can consider new learning applications, mobile devices, course design, learning strategies, and student engagement practices for future studies. Impact on Society: Digitization and global trends are changing how educators teach, and students learn; therefore, gaps need to be continually filled to keep up with the pace of ever-evolving digital technologies that can engage student learning. Future Research: Future research may focus on interactive approaches toward mobile devices in higher education learning and shorter learning activities to engage students.

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.

Action recognition plays a vital role in analysing human body behaviour and has significant implications for research and education. However, traditional recognition methods often suffer from issues such as inaccurate time and spatial feature vectors. Therefore, this study addresses the problem of inaccurate recognition of aerobic gymnastics action image data and proposes a visualised three-dimensional convolutional neural network algorithm-based action recognition model. This model incorporates unsupervised visualisation methods into the traditional network and enhances data recognition capabilities through the introduction of a random noise perturbation enhancement algorithm. The research results indicate that the data augmented with noise perturbation achieves the lowest mean square error, reducing the error value from 0.3352 to 0.3095. The use of unsupervised visualisation analysis enables clearer recognition of human actions, and the algorithm model is capable of accurately recognising aerobic movements. Compared to traditional algorithms, the new algorithm exhibits higher recognition accuracy and superior performance.

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.

With the rapid development of Artificial Intelligence (AI) technology, significant breakthroughs have been made in its application in many fields. Especially, in the field of enterprise human resource management and employee performance evaluation, AI has demonstrated its powerful ability to optimise and improve performance. This study explores the application of AI in enterprise human resource management and how to use AI to evaluate employee performance. The research includes analysing and comparing existing AI-driven human resource management models, evaluating how AI can help improve employee performance and leadership styles, and designing and developing human resource management computer systems for enterprise employees. Through empirical research and case analysis, this study proposes a new AI-optimised employee performance evaluation model and explores its application and effect in practice. In general, the application of AI can improve the efficiency and accuracy of enterprise human resource management, and provide new possibilities for employee performance evaluation. At present, artificial intelligence technology has been widely used in various fields of daily life, especially in corporate human resource management, providing better support for the development of enterprises.

This article presents a case study that outlines the potential of DigiBot technology, an interactive automated response program, in mobile open learning (MOL) for business subjects. The study, which draws on a project implemented in Sub-Saharan Africa, demonstrates the applications of DigiBots delivered via WhatsApp to over 650,000 learners. Employing a mixed-methods approach, the article reports on live event tracking, qualitative observations from facilitators and learning technologists, and a learner survey (<i>N</i> = 304,000). The research offers practical recommendations and proposes a model for scalable DigiBot learning. Findings reveal that in this case, DigiBot MOL had the potential to effectively address two key obstacles in open learning: accessibility and scalability. Leveraging mobile platforms such as WhatsApp mitigates accessibility restrictions, particularly in resource-constrained contexts, while tailored micro-learning enhances scalability.

Aiming to improve the accuracy, recall, and F1 value of data classification, this paper proposes an applied university innovation and entrepreneurship data classification method based on the nearest neighbour criterion. Firstly, the decision tree algorithm is used to mine innovation and entrepreneurship data from applied universities. Then, dynamic weight is introduced to improve the similarity calculation method based on edit distance, and the improved method is used to realise data de-duplication to avoid data over fitting. Finally, the nearest neighbour criterion method is used to classify applied university innovation and entrepreneurship data, and cosine similarity is used to calculate the similarity between the samples to be classified and each sample in the training data, achieving data classification. The experimental results demonstrate that the proposed method achieves a maximum accuracy of 96.5% and an average F1 score of 0.91. These findings indicate a high level of accuracy, recall, and F1 value for data classification using the proposed method.

In order to improve the speedup and recognition accuracy of the recognition process, this paper designs a data mining method based on label mapping for long-term and short-term browsing behaviour of network users. First, after removing the noise information in the behaviour sequence, calculate the similarity of behaviour characteristics. Then, multi-source behaviour data is mapped to the same dimension, and a behaviour label mapping layer and a behaviour data mining layer are established. Finally, the similarity of the tag matrix is calculated based on the similarity calculation results, and the mining results are output using SVM binary classification process. Experimental results show that the acceleration ratio of this method exceeds 0.9; area under curve receiver operating characteristic curve (AUC-ROC) value increases rapidly in a short time, and the maximum value can reach 0.95, indicating that the mining precision of this method is high.

This study investigates the nexus among the commodities: bitcoin, copper, gold, silver, crude oil, and iron ore. Previous studies on establishing the plausibility and the dynamic nexus among commodities are rare. This research attempts to fill this gap. This study investigates whether there are long-term and short-term links between commodities for the period 2010-2022 by applying the bounds testing method to co-integration and ECM, built using an ARDL model and establishing both short-term and long-term relationships among the economic variables analysed. The ECM confirmed the presence of some co-integration relationship for all the variables, both in the short and long term. A strong correlation was discovered among the commodities, which were greatly influenced by their lagged values. The results of this study provides an opportunity for policymakers and researchers to understand the nature of the relationship between the analysed variables and further support the development of new policies for economic sustainability.

The study aims to analyse the impact of shopping applications on the shopping behaviour of the working women community in Bangalore, a city known as the IT hub. The research uses a quantitative analysis with SPSS version 23 software and a structured questionnaire survey technique to gather data from the working women community. The study uses descriptive statistics, ANOVA, regression, and Pearson correlation analysis to evaluate the perception of working women regarding the significance of online shopping applications. The results show that digital shopping applications are more prevalent among the working women community in Bangalore. The study also evaluates the socio-economic and psychological factors that influence their purchasing behaviour. The findings suggest that online marketers should enhance their strategies to improve their business on digital platforms. The research provides valuable insights into the shopping habits of the working women community in Bangalore.