There is a growing interest in the assessment of tangible skills and competence. Specifically, there is an increase in the offerings of competency-based assessments, and some academic institutions are offering college credits for individuals who can demonstrate adequate level of competency on such assessments. An increased interest has been placed on competency-based computer simulations that can assist learners to gain tangible skills. While computer simulations and competency-based projects, in general and particularly in management, have demonstrated great value, there are still limited empirical results on their benefits to e-learners. Thus, we have developed a quasi-experimental research, using a survey instrument on pre- and post-tests, to collect the set of 12 management skills from e-learners attending courses that included both competency-based computer simulations and those that didn’t. Our data included a total of 253 participants. Results show that all 12 management skills measures demonstrated very high reliability. Our results also indicate that all 12 skills of the competency-based computer simulations had higher increase than those that didn’t. Analyses on the mean increases indicated an overall statistically significant difference for six of the 12 management skills enhancements between the experimental and control groups. Our findings demonstrate that overall computer simulations and competency-based projects do provide added value in the context of e-learning when it comes to management skills.

In recent years, schools (as well as universities) have added cyber security to their computer science curricula. This topic is still new for most of the current teachers, who would normally have a standard computer science background. Therefore the teachers are trained and then teaching their students what they have just learned. In order to explore differences in both populations’ learning, we compared measures of software quality and security between high-school teachers and students. We collected 109 source files, written in Python by 18 teachers and 31 students, and engineered 32 features, based on common standards for software quality (PEP 8) and security (derived from CERT Secure Coding Standards). We use a multi-view, data-driven approach, by (a) using hierarchical clustering to bottom-up partition the population into groups based on their code-related features and (b) building a decision tree model that predicts whether a student or a teacher wrote a given code (resulting with a LOOCV kappa of 0.751). Overall, our findings suggest that the teachers’ codes have a better quality than the students’ – with a sub-group of the teachers, mostly males, demonstrate better coding than their peers and the students – and that the students’ codes are slightly better secured than the teachers’ codes (although both populations show very low security levels). The findings imply that teachers might benefit from their prior knowledge and experience, but also emphasize the lack of continuous involvement of some of the teachers with code-writing. Therefore, findings shed light on computer science teachers as lifelong learners. Findings also highlight the difference between quality and security in today’s programming paradigms. Implications for these findings are discussed.

Objective: Evaluate the effectiveness of distance learning courses for the purpose of interdisciplinary continuing education in Speech Pathology and Dentistry. Methods: The online course was made available on the Moodle platform. A total of 30 undergraduates participated in the study (15 from the Dentistry course and 15 from the Speech Pathology course). Their knowledge was evaluated before and after the course, in addition to the user satisfaction by means of specific questionnaires. The course was evaluated by 6 specialists on the following aspects: presentation and quality of the content, audio-visual quality, adequacy to the target public, and information made available. To compare the obtained results in the pre- and post-course questionnaires, the test Wilcoxon was carried out, with a 5% significance level. Results: the teaching/learning process, including the theoretical/practical application for the interdisciplinary training, proved to be effective as there was a statistically significant difference between the pre- and post- course evaluations (p<0.001), the users’ satisfaction degree was favorable and the specialists evaluated the material as adequate regarding the target public, the audio-visual information quality and the strategies of content availability. Conclusion: The suggested distance-learning course proved to be effective for the purpose of Speech Pathology and Dentistry interdisciplinary education.

Teaching object-oriented programming to students in an in-classroom environment demands well-thought didactic and pedagogical strategies in order to guarantee a good level of apprenticeship. To teach it on a completely distance learning environment (e-learning) imposes possibly other strategies, besides those that the e-learning model of Open University of Portugal dictates. This article analyses the behavior of the students of the 1st cycle in Computer Science while interacting with the object-oriented programming (OOP) discipline available to them on the Moodle platform. Through the evaluation of the level of interaction achieved in a group of relevant selected actions by the students, it is possible to identify their relevancy to the success of the programming learning process. Data was extracted from Moodle, numerically analyzed, and, with the use of some charts, behavior patterns of students were identified. This paper points out potential new approaches to be considered in e-learning in order to enhance programming learning results, besides confirming a high level of drop-out and a low level of interaction, thus finding no clear correlation between students’ success and the number of online actions (especially in forums), which reveals a possible failure of the main pillar on which the e-learning model relies.

This paper reports on a case study of a group of six non-native English speaking migrant women’s experiences learning English vocabulary in a mobile assisted language learning (MALL) environment at a small community centre in Western Australia. A sociocultural approach to learning vocabulary was adopted in designing the MALL lessons that the women undertook. The women provided demographic information, responded to questions in a pre-MALL semi-structured interview, attended the MALL lessons, and completed a post-MALL semi-structured interview. This study explores the sociocultural factors that affect migrant women’s language learning in general, and vocabulary in particular. The women’s responses to MALL lessons and using the tablet reveal a positive effect in their vocabulary learning.

The current rapid technological changes confront researchers of learning technologies with the challenge of evaluating them, predicting trends, and improving their adoption and diffusion. This study utilizes a data-driven discourse analysis approach, namely culturomics, to investigate changes over time in the research of learning technologies. The patterns and changes were examined on a corpus of articles published over the past decade (2006-2014) in the proceedings of Chais Conference for the Study of Innovation and Learning Technologies – the leading research conference on learning technologies in Israel. The interesting findings of the exhaustive process of analyzing all the words in the corpus were that the most commonly used terms (e.g., pupil, teacher, student) and the most commonly used phrases (e.g., face-to-face) in the field of learning technologies reflect a pedagogical rather than a technological aspect of learning technologies. The study also demonstrates two cases of change over time in prominent themes, such as “Facebook” and “the National Information and Communication Technology (ICT) program”. Methodologically, this research demonstrates the effectiveness of a data-driven approach for identifying discourse trends over time.

CAPTCHA is one of the most common solutions to check if the user trying to enter a Website is a real person or an automated piece of software. This challenge-response test, implemented in many Internet Websites, emphasizes the gaps between accessibility and security on the Internet, as it poses an obstacle for the learning-impaired in the reading and comprehension of what is presented in the test. Various types of CAPTCHA tests have been developed in order to address accessibility and security issues. The objective of this study is to investigate how the differences between various CAPTCHA tests affect user experience among populations with and without learning disabilities. A questionnaire accompanied by experiencing five different tests was administered to 212 users, 60 of them with learning disabilities. Response rates for each test and levels of success were collected automatically. Findings suggest that users with learning disabilities have more difficulties in solving the tests, especially those with distorted texts, have more negative attitudes towards the CAPTCHA tests, but the response time has no statistical difference from users without learning disabilities. These insights can help to develop and implement solutions suitable for many users and especially for population with learning disabilities.

This is a five-year study conducted with junior high school students studying in a 1:1-laptop program in order to test the effects of the program on various measures related to the students: their attitudes, motivation, perceived school norms, self-efficacy, and behavioral intention towards learning with laptops, according to the Theory of Planned Behavior (TPB). These variables were tested at two dimensions: ‘duration of learning’ – the effect of learning in the program on the same students; ‘duration of program in school’ – the effect of the program on different students in different school years. Participants (N=770) answered a questionnaire structured according to motivational and TPB variables. Findings show that attitudes changed over time, but differently for each dimension. For the ‘duration of learning’, attitudes declined between 7th to 9th grade. Structural equation modeling analysis showed that students’ attitudes and self-efficacy explain part of their intention to learn with laptops, therefore ways of maintaining positive attitudes, self-efficacy, and strengthening school norms should be considered. However, for the ‘duration of program in school’, students’ attitudes increased over the years: The attitudes of students who started the program at a later stage were more positive than those who began earlier. This may indicate that students who experience the program at an advanced stage are better prepared, with more realistic expectations. Findings can assist teacher trainers and policymakers with the implementation of similar programs.

This paper provides an overview of the impact that social media has on the development of collaborative learning within a cohort environment in a doctoral program. The researchers surveyed doctoral students in an education program to determine how social media use has influenced the doctoral students. The study looked at the following areas: a) the ability of social media use to develop a collaborative learning environment, b) access to social media content which supports learning, and c) whether social media use has contributed to the enhancement of the doctoral students’ academic achievement and learning progress. As social media use and on-line learning become more prevalent in education, it is important to continue to understand the impact that social media has on improving students’ ability to achieve their academic goals. This study provides insight on how doctoral students used social media and how social media use has influenced academic development in their cohort environment. In addition, this paper provides a discerning view into the role social media plays when developing a collaborative learning environment in a cohort.

Learning objects originally developed for use in online learning environments can also be used to enhance face-to-face instruction. This study examined the learning impacts of online learning objects packaged into modules and used in different contexts for undergraduate education offered on campus at three institutions. A multi-case study approach was used, examining learning impacts across a variety of course subjects, course levels (introductory and advanced undergraduate), student levels (undergraduate and graduate), and instructional goals (i.e., replacement for lecture, remediation). A repeated measures design was used, with learning data collected prior to viewing the online module, after completion of the module, and at the end of the semester. The study provided a broad examination of ways that online modules are typically used in a college classroom, as well as measured learning effectiveness based on different instructional purpose and usage contexts. Results showed the effectiveness of the modules in serving as a substitute for classroom lecture, remediation of course prerequisite material, introduction to content with follow-up lab practice, and review for final exams. In each of these cases, the use of the modules resulted in significant learning increases, as well as retention of the learning until the end of the semester.

As a result of the rapid development of Information and Communication Technology (ICT) and the growing interest in Internet-based tools for language classroom, it has become a pressing need for educators to locate, evaluate and select the most appropriate language-learning digital resources that foster more communicative and meaningful learning processes. Hence, this paper describes a mixed research project that, on the first hand, aimed at proposing a Checklist for evaluating language websites built on the principles of the Communicative Approach, and on the second hand, sought to strengthen the teachers’ Knowing-how-to-do skill as part of their digital competence. To achieve these goals, a four-phase research procedure was followed that included reviewing relevant literature and administering qualitative and quantitative research methods to participants (i.e., language teachers, an expert in the Computer-Assisted Language Learning (CALL) field and a college professor) in order to gain insights into problematic issues and, thereafter, to contribute to the creation and validation of the Checklist model and the Study Guide. The findings revealed that: (a) evaluating language websites leads to the enhancement of the teachers’ practical skills and their knowledge of the technological language; and (b) having an assessment instrument allows educators to choose the materials that best meet their communicative teaching purposes.

Personalization is one of the most expected features in the current educational systems. User modeling is supposed to be the first stage of this process, which may incorporate learning style as an important part of the model. Learning style, which is a non-stable characteristic in the case of children, differentiates students in learning preferences. This paper identifies a new hybrid method to initiate and update the information of children’s learning style in an educational system. At the start-up phase, children’s learning style information is gathered through the modified Murphy-Meisgeier Type Indicator for Children (MMTIC) questionnaire, which is based on the well-known Myers-Briggs Type Indicator (MBTI). This primary information will be tuned by tracking children’s behaviors during the learning process. Analytical data mining helped us to cluster these behaviors and find their patterns. The proposed method was applied on 81 fourth grade children in elementary school. Delivering results suggest that this method provides a good precision in recognizing children learning style and may be an appropriate solution for non-stability problems in their preferences.

Aim/Purpose: As online video lectures rapidly gain popularity in formal and informal learning environments, one of their main challenges is student retention. This study investigates the influence of adding interactivity to online video lectures on students’ attention span. Background: Interactivity is perceived as increasing the attention span of learners and improving the quality of learning. However, interactivity may be regarded as an interruption, which distracts students. Furthermore, adding interactive elements to online video lectures requires additional investment of various resources. Therefore, it is important to investigate the impact of adding interactivity to online video lectures on the attention span of learners. Methodology: This study employed a learning analytics approach, obtained data from Google Analytics, and analyzed data of two Massive Open Online Courses (MOOCs) that were developed by the Open University of Israel in order to make English for academic purposes (EAP) courses freely accessible. Contribution: The paper provides important insights, based on quantitative empirical research, on: integrating interactive elements in online videos; the impact of video length; and differences between two groups of advanced and basic learners. Furthermore, it demonstrates how learning analytics may be used for improving instructional design. Findings: The findings suggest that interactivity may increase the attention span of learners, as measured by the average online video lecture viewing completion percentage, before and after the addition of interactivity. However, when the lecture is longer than about 15 minutes, the completion percentages decrease, even after adding interactive elements. Recommendations for Practitioners: Adding interactivity to online video lectures and controlling their length is expected to increase the attention span of learners. Recommendation for Researchers: Learning analytics is a powerful quantitative methodology for identifying ways to improve learning processes. Impact on Society: Providing practical insights on mechanisms for increasing the attention span of learners is expected to improve social inclusion. Future Research: Discovering further best practices to improve the effectiveness of online video lectures for diverse learners.

Aim/Purpose: To develop a framework for utilizing Mobile Assisted Language Learning (MALL) to assist non-native English migrant women to acquire English vocabulary in a non-formal learning setting. Background: The women in this study migrated to Australia with varied backgrounds including voluntary or forced migration, very low to high levels of their first language (L1), low proficiency in English, and isolated fulltime stay-at-home mothers. Methodology: A case study method using semi-structured interviews and observations was used. Six migrant women learners attended a minimum of five non-MALL sessions and three participants continued on and attended a minimum of five MALL sessions. Participants were interviewed pre- and post-sessions. Data were analysed thematically. Contribution: The MALL framework is capable of enriching migrant women’s learning experience and vocabulary acquisition. Findings: Vocabulary acquisition occurred in women from both non-MALL and MALL environment; however, the MALL environment provided significantly enriched vocabulary learning experience. Future Research: A standardised approach to measure the effectiveness of MALL for vocabulary acquisition among migrant women in non-formal setting

Aim/Purpose: These days educators are expected to integrate technological tools into classes. Although they acquire relevant skills, they are often reluctant to use these tools. Background: We incorporated online forums for generating a Community of Inquiry (CoI) in a faculty development program. Extending the Technology, Pedagogy, and Content Knowledge (TPACK) model with Assessment Knowledge and content analysis of forum discourse and reflection after each CoI, we offer the Diagnostic Tool for Learning, Assessment, and Research (DTLAR). Methodology: This study spanned over two cycles of a development program for medical faculty. Contribution: This study demonstrates how the DTLAR supports in-depth examination of the benefits and challenges of using CoIs for learning and teaching. Findings: Before the program, participants had little experience with, and were reluctant to use, CoIs in classes. At the program completion, many were willing to adopt CoIs and appreciated this method’s contribution. Both CoIs discourse and reflections included positive attitudes regarding cognitive and teacher awareness categories. However, negative attitudes regarding affective aspects and time-consuming aspects of CoIs were exposed. Participants who experienced facilitating a CoI gained additional insights into its usefulness. Recommendations for Practitioners : The DTLAR allows analyzing adaption of online forums for learning and teaching. Recommendation for Researchers: The DTLAR allows analyzing factors that affect the acceptance of online fo-rums for learning and teaching. Impact on Society : While the tool was implemented in the context of medical education, it can be readily applied in other adult learning programs. Future Research: The study includes several design aspects that probably affected the improve-ment and challenges we found. Future research is called for providing guidelines for identifying boundary conditions and potential for further improvement.

Aim/Purpose: This study examines differences in credit and noncredit users’ learning and usage of the Plant Sciences E-Library (PASSEL, http://passel.unl.edu), a large international, open-source multidisciplinary learning object repository. Background: Advances in online education are helping educators to meet the needs of formal academic credit students, as well as informal noncredit learners. Since online learning attracts learners with a wide variety of backgrounds and intentions, it is important understand learner behavior so that instructional resources can be designed to meet the diversity of learner motivations and needs. Methodology: This research uses both descriptive statistics and cluster analysis. The descriptive statistics address the research question of how credit learners differ from noncredit learners in using an international e-library of learning objects. Cluster analysis identifies high and low credit/noncredit students based on their quiz scores and follow-up descriptive statistics to (a) differentiate their usage patterns and (b) help describe possible learning approaches (deep, surface, and strategic). Contribution: This research is unique in its use of objective, web-tracking data and its novel use of clustering and descriptive analytic approaches to compare credit and noncredit learners’ online behavior of the same educational materials. It is also one of the first to begin to identify learning approaches of the noncredit learner. Findings: Results showed that credit users scored higher on quizzes and spent more time on the online quizzes and lessons than did noncredit learners, suggesting their academic orientation. Similarly, high credit scorers spent more time on individual lessons and quizzes than did the low scorers. The most striking difference among noncredit learners was in session times, with the low scorers spending more time in a session, suggesting more browsing behavior. Results were used to develop learner profiles for the four groups (high/low quiz scorers x credit/noncredit). Recommendations for Practitioners: These results provide preliminary insight for instructors or instructional designers. For example, low scoring credit students are spending a reasonable amount of time on a lesson but still score low on the quiz. Results suggest that they may need more online scaffolding or auto-generated guidance, such as the availability of relevant animations or the need to review certain parts of a lesson based on questions missed. Recommendation for Researchers: The study showed the value of objective, web-tracking data and novel use of clustering and descriptive analytic approaches to compare different types of learners. One conclusion of the study was that this web-tracking data be combined with student self-report data to provide more validation of results. Another conclusion was that demographic data from noncredit learners could be instrumental in further refining learning approaches for noncredit learners. Impact on Society: Learning object repositories, online courses, blended courses, and MOOCs often provide learners the option of moving freely among educational content, choosing not only topics of interest but also formats of material they feel will advance their learning. Since online learning is becoming more prolific and attracts learners with a wide variety of backgrounds and intentions, these results show the importance of understanding learner behavior so that e-learning instructional resources can be designed to meet the diversity of learner motivations and needs. Future Research: Future research should combine web-tracking data with student self-report to provide more validation of results. In addition, collection of demographic data and disaggregation of noncredit student usage motivations would help further refining learning approaches for this growing population of online users.

Aim/Purpose: This study examines the influence of Performance Expectancy (PE), Effort Expectancy (EE), and Facilitating Conditions (FC) on the use of smart phones for mobile learning by postgraduate students in University of Ibadan, Nigeria. Background: Due to the low level of mobile learning adoption by students in Nigeria, three base constructs of the Unified Theory of Acceptance and Use of Technology (UTAUT) model were used as factors to determine smart phone use for mobile learning by the postgraduate students in the University of Ibadan. Methodology: The study adopted a descriptive survey research design of the correlational type, the two-stage random sampling technique was used to select a sample size of 217 respondents, and a questionnaire was used to collect data. Descriptive statistics (frequency counts, percentages, mean, and standard deviation), test of norm, and inferential statistics (correlation and regression analysis) were used to analyze the data collected. Contribution: The study empirically validated the UTAUT model as a model useful in predicting smart phone use for mobile learning by postgraduate students in developing countries. Findings: The study revealed that a significant number of postgraduate students used their smart phones for mobile learning on a weekly basis. Findings also revealed a moderate level of Performance Expectancy (???? =16.97), Effort Expectancy (???? =12.57) and Facilitating Conditions (???? =15.39) towards the use of smart phones for mobile learning. Results showed a significant positive relationship between all the independent variables and use of smart phones for mobile learning (PE, r=.527*; EE, r=.724*; and FCs, r=.514*). Out of the independent variables, PE was the strongest predictor of smart phone use for mobile learning (β =.189). Recommendations for Practitioners: Librarians in the university library should organize periodic workshops for postgraduate students in order to expose them to the various ways of using their smart phones to access electronic databases. Recommendation for Researchers: There is a need for extensive studies on the factors influencing mobile technologies adoption and use in learning in developing countries. Impact on Society: Nowadays, mobile learning is increasingly being adopted over conventional learning systems due to its numerous benefits. Thus, this study provides an insight into the issues influencing the use of smart phones for mobile learning by postgraduate students from developing countries. Future Research: This study utilized the base constructs of the UTAUT model to determine smart phone use for mobile learning by postgraduate students in a Nigerian university. Subsequent research should focus on other theories to ascertain factors influencing Information Technology adoption and usage by students in developing countries.

Aim/Purpose: This paper presents the preliminary findings of a pilot survey that sought to examine the technology uses, backgrounds, needs, interests, career goals, and professional expectations of Generation Z students enrolled at a minority serving institution in the United States Mid-Atlantic region. Background: Students entering college today are part of Generation Z born in the late 90’s through 2016. Known for their short attention spans and heightened ability to multi-task, they already outnumber millennials and are the first true digital natives born during the age of smart phone. Methodology: In the fall of 2017, an online student perception survey was piloted with stu-dents enrolled at a mid-Atlantic minority serving institution. The survey included a combination of dichotomous, Likert-scaled, and ranking questions. The survey was administered electronically using the Survey Monkey system to students following completion of core computer concepts courses and explored their technology backgrounds, skills, perceived computing self-efficacy, and the role they predict technology will play in their future career. The data was subsequently exported to Microsoft Excel and SPSS where descriptive statistical analyses were conducted. Contribution: As Generation Z descends on college campuses, with their technology domi-nated backgrounds and different communications, learning, and social prefer-ences, it is important to better understand this generation whose needs and expectations will help shape the future of higher education. Additionally, this study also provides research on a population (first-generation minority college students) that is expanding in numbers in higher education and that the litera-ture, reports is impacted negatively by the digital divide and educational inequalities. This paper is timely and relevant and helps to extend our understanding of Generation Z. Findings: The findings show that Generation Z learners enrolled in a minority-serving institution enjoy computer classes, feel that using computers comes easy to them; and perceive themselves as experts in the use of social media, mobile operating systems, using a smart phone, searching the Web, and email. Participants also reported that they want to be more technologically literate, want to be more skilled in computer software applications, and are interested in learning about cyber security. In terms of the future, most respondents also believe that their career will require them to analyze information to inform decision making. Additionally, most stated that information security will be important to their future career. Finally, the results affirmed that college computing courses remain important and that college students recognize that technology will play a crucial role in their career with employers wanting to see job applicants with strong technology skills. Recommendations for Practitioners: Generation Z learners enrolled in higher education need, and want, a wide range of technology courses available to them in order to help them meet the rapidly evolving demands of tomorrow’s workplace. Students in this study overwhelmingly see the value in enhancing their technology skills especially in such areas as computer software applications, information management, and cyber security. Recommendation for Researchers: Institutions of higher education should invest in thorough and ongoing examinations of the information and technology literacy skills, needs, and perceptions of students. Impact on Society: Understanding the interests and needs of Generation Z learners is imperative to the future of higher education. Future Research: This survey is a work in progress that is part of a pilot study that is being used to help guide a much more sizable examination of Generation Z learners.

Aim/Purpose: Most research on work-based learning and research relates to theory, including perspectives, principles and curricula, but few studies provide contemporary examples of work-based projects, particularly in the Australian context; this paper aims to address that limitation. Background: The Professional Studies Program at University of Southern Queensland is dedicated to offering advanced practice professionals the opportunity to self-direct organizational and work-based research projects to solve real-world workplace problems; two such examples in the Australian context are provided by this paper. Methodology: The paper employs a descriptive approach to analyzing these two work-based research projects and describes the mixed methods used by each researcher. Contribution: The paper provides examples of work-based research in (a) health, safety, and wellness leadership and its relation to corporate performance; and (b) investigator identity in the Australian Public Service; neither topic has been examined before in Australia and little, if anything, is empirically known about these topics internationally. Findings: The paper presents the expected outcomes for each project, including discussion of the ‘triple dividend’ of personal, organizational, and practice domain benefits; as importantly, the paper presents statements of workplace problems, needs and opportunities, status of the practice domain, background and prior learning of the researchers, learning objectives, work-based research in the practice domain, and lessons learned from research which can be integrated into a structured framework of advanced practice. Recommendations for Practitioners: This is a preliminary study of two work-based research projects in Australia; as these and other real-world projects are completed, further systematic and rigorous reports to the international educational community will reveal the granulated value of conducting projects designed to change organisations and concordant practice domains. Recommendation for Researchers: While introducing the basic elements of research methods and expected out-comes of work-based projects, examples in this paper give only a glimpse into the possible longer-term contributions such research can make to workplaces in Australia. Researchers, as a consequence, need to better understand the relationship between practice domains, research as a valuable investigative tool in workplaces, and organizational and social outcomes. Impact on Society: Work-based learning and research have been developed to not only meet the complex and changing demands of the global workforce but have been implemented to address real-world organizational problems for the benefit of society; this paper provides two examples where such benefit may occur. Future Research: Future research should focus on the investigation of triple-dividend outcomes and whether they are sustainable over the longer term.

Aim/Purpose: Work-based learning has been identified in the literature, and is established in academia and in the global worlds of work; however, an examination of work-based research, particularly at the doctoral level, has been less well articulated. Moreover, a paucity of published literature on either work-based research or Professional Studies means little is known about the dynamics and drivers of these domains. This study aims to begin addressing the shortfall in literature on work-based research and Professional Studies programs, using the program at University of Southern Queensland as an example Background: This paper examines work-based research in the context of the Professional Studies program at University of Southern Queensland in Australia, with which the authors are affiliated. Methodology: Analysis of work-based research includes discussion of ‘messy’ research environments and the changing nature of workplaces, along with the opportunities and challenges such environments pose for action researchers. Contribution: In addition to addressing a shortfall in the published literature on work-based research, the paper also contributes insight into the mechanisms used to promote reflective practice and the generation of professional artefacts. Findings: Often driven by altruism, work-based research as implemented in the Professional Studies program results in a so-called ‘triple dividend’, designed to benefit the individual researcher, work environment, and community of practice. Recommendations for Practitioners: To be successful contributors to work-based research, practitioners need to reflect carefully and deeply on experience, planning and outcomes, using what in this paper we call ‘micro-reflective’ (personal) and ‘macro-reflective’ (program) cycles of reflection. Recommendation for Researchers: In addition to generating new knowledge and expanding the frontiers of workplaces, work-based research is often motivated by complicated and wide-reaching imperatives; work-based researchers therefore need to consider the goals, objectives, priorities and vision of their work environments, as well as understand issues related to bias, ethical practice and the nature of insider research. Impact on Society: Work-based learning and research address the complexities, challenges and future demands of Australian workplaces along with the work, mobility and personal development needs of mid- to senior-career professionals. Future Research: In addition to the multitude of action research programs possible in work-places in Australia, more research is needed to understand higher education work-based learning and its relation to, and impact on, work-based research, particularly when applying mixed methods research to work environments.

Aim/Purpose: The aim of the research was to examine the relationship between the sub-dimensions of organizational culture perceptions, such as task culture, success culture, support culture, and bureaucratic culture and job motivations of ISMEK Lifelong Learning Center teachers. Background: It is thought that if teachers’ perceptions of organizational culture and levels of job motivation are assessed and the effects of school culture on the motivation level of teachers investigated, solutions to identified problems can be developed. Methodology: The study was conducted using survey research. The sample population consisted of 354 teachers working for the Istanbul Metropolitan Municipality’s Lifelong Learning Center (ISMEK). The personal information form prepared by the researchers, the School Culture Scale developed by Terzi (2005) and the Job Motivation Scale developed by Aksoy (2006) were administered to the teachers. Contribution: This study will contribute to research on the job motivations of teachers involved in adult education. Findings: The findings indicated that task culture differs according to gender. Teachers report high levels of job motivation, but job motivation varies with gender, education level, and number of years working at the ISMEK Lifelong Learning Center. A significant relationship was found between sub-dimensions of organizational culture and job motivation. Organizational culture explains more than half of the change in job motivation. The sub-dimensions of organizational culture, task culture, achievement culture, and support culture were found to be significantly predictive of job motivation. Recommendations for Practitioners: In order to increase motivation of teachers, a success-oriented structure should be formed within the organization. It is necessary for teachers and managers to support each other and to establish a support culture in their institutions. In order to establish a culture of support, managers need to receive in-service training. Recommendation for Researchers: This study was carried out in the ISMEK Lifelong Learning Center and similar studies can be done in classrooms, training centers, and study centers. Impact on Society: Teachers working in adult education should be afforded a more comfortable working environment that will positively impact job motivation, resulting in a higher quality of education for students. Therefore, this research may contribute to an increase in the number of students who engage in lifelong learning opportunities. Future Research: This qualitative study utilized a relational survey model. A more in-depth qualitative study employing observation and interviews is warranted.

Technology has transformed education, perhaps most evidently in course delivery options. However, compelling questions remain about how technology impacts learning. Adaptive learning tools are technology-based artifacts that interact with learners and vary presentation based upon that interaction. This paper compares adaptive learning with a conventional teaching approach implemented in a digital literacy course. Current research explores the hypothesis that adapting instruction to an individual’s learning style results in better learning outcomes. Computer technology has long been seen as an answer to the scalability and cost of individualized instruction. Adaptive learning is touted as a potential game-changer in higher education, a panacea with which institutions may solve the riddle of the iron triangle: quality, cost and access. Though the research is scant, this study and a few others like it indicate that today’s adaptive learning systems have negligible impact on learning outcomes, one aspect of quality. Clearly, more research like this study, some of it from the perspective of adaptive learning systems as informing systems, is needed before the far-reaching promise of advanced learning systems can be realized.

Aim/Purpose Information Technology students’ learning outcomes improve when teaching methodology moves away from didactic behaviorist-based pedagogy toward a more heuristic constructivist-based version of andragogy. Background There is a distinctive difference, a notable gap, between the academic community and the business community in their views of the level of preparedness of recent information technology program graduates. Understanding how Information Technology curriculum is developed and taught along with the underpinning learning theory is needed to address the deficient attainment of learning outcomes at the heart of this matter. Methodology The case study research methodology has been selected to conduct the inquiry into this phenomenon. This empirical inquiry facilitates exploration of a contemporary phenomenon in depth within its real-life context using a variety of data sources. The subject of analysis will be two Information Technology classes composed of a combination of second year and third year students; both classes have six students, the same six students. Contribution It is the purpose of this research to show that the use of improved approaches to learning will produce more desirable learning outcomes. Findings The results of this inquiry clearly show that the use of the traditional behaviorist based pedagogic model to achieve college and university IT program learning outcomes is not as effective as a more constructivist based andragogic model. Recommendations Instruction based purely on either of these does a disservice to the typical college and university level learner. The correct approach lies somewhere in between them; the most successful outcome attainment would be the product of incorporating the best of both. Impact on Society Instructional strategies produce learning outcomes; learning outcomes demonstrate what knowledge has been acquired. Acquired knowledge is used by students as they pursue professional careers and other ventures in life. Future Research Learning and teaching approaches are not “one-size-fits-all” propositions; different strategies are appropriate for different circumstances and situations. Additional research should seek to introduce vehicles that will move learners away from one the traditional methodology that has been used throughout much of their educational careers to an approach that is better suited to equip them with the skills necessary to meet the challenges awaiting them in the professional world.

Aim/Purpose: The aim of this paper is to propose an ensemble learners based classification model for classification clickbaits from genuine article headlines. Background: Clickbaits are online articles with deliberately designed misleading titles for luring more and more readers to open the intended web page. Clickbaits are used to tempted visitors to click on a particular link either to monetize the landing page or to spread the false news for sensationalization. The presence of clickbaits on any news aggregator portal may lead to an unpleasant experience for readers. Therefore, it is essential to distinguish clickbaits from authentic headlines to mitigate their impact on readers’ perception. Methodology: A total of one hundred thousand article headlines are collected from news aggregator sites consists of clickbaits and authentic news headlines. The collected data samples are divided into five training sets of balanced and unbalanced data. The natural language processing techniques are used to extract 19 manually selected features from article headlines. Contribution: Three ensemble learning techniques including bagging, boosting, and random forests are used to design a classifier model for classifying a given headline into the clickbait or non-clickbait. The performances of learners are evaluated using accuracy, precision, recall, and F-measures. Findings: It is observed that the random forest classifier detects clickbaits better than the other classifiers with an accuracy of 91.16 %, a total precision, recall, and f-measure of 91 %.

Aim/Purpose: To discuss the Design Science Research approach by comparing some of its canons with observed practices in projects in which it is applied, in order to understand and structure it better. Background: Recent criticisms of the application of the Design Science Research (DSR) approach have pointed out the need to make it more approachable and less confusing to overcome deficiencies such as the unrealistic evaluation. Methodology: We identified and analyzed 92 articles that presented artifacts developed from DSR projects and another 60 articles with preceding or subsequent actions associated with these 92 projects. We applied the content analysis technique to these 152 articles, enabling the preparation of network diagrams and an analysis of the longitudinal evolution of these projects in terms of activities performed and the types of artifacts involved. Contribution: The content analysis of these 152 articles enabled the preparation of network diagrams and an analysis of the longitudinal evolution of these projects in terms of the activities and types of artifacts involved. Evidence was found of a precedence hierarchy among different types of artifacts, as well as nine new opportunities for entry points for the continuity of DSR studies. Only 14% of the DSR artifacts underwent an evaluation by typical end users, characterizing a tenth type of entry point. Regarding the evaluation process, four aspects were identified, which demonstrated that 86% of DSR artifact evaluations are unrealistic. Findings: We identified and defined a set of attributes that allows a better characterization and structuring of the artifact evaluation process. Analyzing the field data, we inferred a precedence hierarchy for different artifacts types, as well as nine new opportunities for entry points for the continuity of DSR studies. Recommendation for Researchers: The four attributes identified for analyzing evaluation processes serve as guidelines for practitioners and researchers to achieve a realistic evaluation of artifacts. Future Research: The nine new entry points identified serve as an inspiration for researchers to give continuity to DSR projects.

Aim/Purpose: In this paper we propose an ecosystem for translational learning that combines core learning principles with a multilevel construct that embraces the tenets of translational research, namely, teaming, translating, and implementing. The goal of the paper is to argue that knowledge of learning sciences is essential at the individual, team, and organizational levels in the translational science enterprise. Background: The two decades that we can now call the translational era of health and medicine have not been without challenges. Many inroads have been made in navigating how scientific teaming, translating knowledge across the health spectrum, and implementing change to our health systems, policies, and interventions can serve our changing global environment. These changes to the traditional health science enterprise require new ways of understanding knowledge, forging relationships, and managing this new tradition of science. Competency requirements that have become important to the enterprise are dependent on a deep understanding about how people learn as individuals, in teams, and within organizations and systems. Methodology: An individual, team, and organizational conceptual framework for learning in translational ecosystems is developed drawing on the learning science literature, a synthesis of 9 key learning principles and integrated with core competencies for translational science. Contribution: The translational learning ecosystem is a means by which to understand how translational science competencies can be reinforced by core learning principles as teaming, translating, and implementation intersect as part of the translational science enterprise. Findings: This paper connects learning science to tailored principles in a simplified way so that those working translational science with less knowledge of theories of learning and pedagogy may be able to access it in a clear and concise way. Recommendation for Researchers: This paper provides a framework for researchers who engage in the education of translational scientists as well as those who are charged with training new scientists in an emerging field critical to health and medicine. Future Research: The translational ecosystem described can serve to expand how teaching and learning impact scientific advances. In addition, it serves as a means in which to understand the impact of learning on micro, meso, and macro levels.

Aim/Purpose: The amount of information published has increased dramatically due to the information explosion. The issue of managing information as it expands at this rate lies in the development of information extraction technology that can turn unstructured data into organized data that is understandable and controllable by computers Background: The primary goal of named entity recognition (NER) is to extract named entities from amorphous materials and place them in pre-defined semantic classes. Methodology: In our work, we analyze various machine learning algorithms and implement K-NN which has been widely used in machine learning and remains one of the most popular methods to classify data. Contribution: To the researchers’ best knowledge, no published study has presented Named entity recognition for the Kikuyu language using a machine learning algorithm. This research will fill this gap by recognizing entities in the Kikuyu language. Findings: An evaluation was done by testing precision, recall, and F-measure. The experiment results demonstrate that using K-NN is effective in classification performance. Recommendation for Researchers: With enough training data, researchers could perform an experiment and check the learning curve with accuracy that compares to state of art NER. Future Research: Future studies may be done using unsupervised and semi-supervised learning algorithms for other resource-scarce languages.

Aim/Purpose: The purpose of this study is to determine the impact of pre-listening activities on Arabic-speaking EFL learners’ comprehension of spoken texts. Background: This study aims to contribute to the current research and to increase our understanding about the effectiveness of pre-listening activities. Specifically, this study seeks to clarify some of the research in this area that seems to be incongruent. Methodology: The study investigates two widely implemented activities in second language (L2) classrooms: vocabulary preteaching and content previewing. Ninety-three native-Arabic speaking EFL learners, whose proficiently levels were beginner, intermediate, or advanced, were randomly assigned to a control group or one of three experimental groups: the vocabulary-only (VO) group, content-only (CO) group, or vocabulary + content (VC) group. Each of the experimental groups received one of the treatments to determine which pre-listening activity was more effective and whether additional pre-listening activities yield additional comprehension. Listening comprehension of the aural text was measured by a test comprising 13 multiple-choice and true-false questions. Contribution: The present study provided additional explanations regarding the long-standing contradicting results about vocabulary preteaching and content previewing. Findings: The results showed that pre-listening activities had a positive impact on Arabic-speaking EFL learners’ listening comprehension, with the VO group significantly increasing their scores on the posttest compared to those of the control or other groups. Vocabulary preteaching was particularly beneficial for more advanced learners. With regard to which pre-listening activity contributed the most to better listening comprehension, vocabulary preteaching was the most effective. Content previewing did not increase comprehension for the CO group and had no additional benefit for the VC group. Recommendation for Researchers: This paper recommends that researchers explore new pre-listening activities that have never studied. Future research should be extended to include other nations and contextual situations to extend our knowledge about the effect of pre-listening activities. As far as listening comprehension can only be achieved when listeners are attentive and engaged, the listening text should be interesting and the lexical coverage of the listening text should be appropriate for all participants. Future Research: The results are to be interpreted carefully because they are limited by the students’ L2 proficiency, demographic, and cultural backgrounds (i.e., first language (L1) proficiency, age, gender, Middle Eastern culture). Results might be quite different if the study was conducted with different populations who have different life and language learning experiences (Vandergrift & Baker, 2015). Therefore, the results of this study indicate there is much room for improvement and a need for further research.