Massive open online courses (MOOCs) in genomic variant interpretation: An innovative education strategy for the growing genetic counselor workforce.

The growth in genomic testing in healthcare requires a highly trained specialist workforce to ensure evidence based clinical germline variant interpretation. Genetic counselors form a core part of the clinical genomics multidisciplinary team (MDT) and represent a growing workforce participating in variant interpretation from data analysis to the patient consultation. Standardized, high-quality variant interpretation training for Genetic Counselors has historically been ad hoc and variable, with existing programs lacking capacity to reach the entire workforce. To address the requirement for scalable variant interpretation training for genomics healthcare professionals (HCPs), two Massive Open Online Courses (MOOCs) were developed. We analyzed the data from 17 Genetic counselors, as part of an evaluation cohort completing the first run of these MOOCs. Overall genetic counselors enjoyed the courses, felt they were clinically relevant and would recommend them to colleagues. Common challenges amongst the genetic counseling workforces included utilizing relevant databases and finding time in the workday to complete training. These findings suggest MOOCs could be an acceptable option to ensure a consistent and transferrable high standard of training, complimentary to existing curricula. They also hold the potential to facilitate large-scale education to update the genetic counseling workforce when changes in variant interpretation guidance occur.

Investigating the acceptance and use of massive open online courses (MOOCs) for health informatics education.

BACKGROUND: This study investigated the acceptance and use of massive open online courses (MOOCs) among health informatics educators and students in Saudi Arabian academic institutions. A theoretical model based on the unified theory of acceptance and use of technology (UTAUT), self-determination theory (SDT), and channel expansion theory (CET) was used to identify factors that affect MOOC adoption in health informatics education. METHODS: A survey research design was employed, and cross-sectional data were collected from health informatics instructors and students in academic institutions in Saudi Arabia. A total of 145 completed responses were used in the final analysis of the data. RESULTS: The findings indicated that performance and effort expectancy were important factors that could predict the acceptance and use of MOOCs among health informatics instructors and students. Additionally, perceived media richness affected the actual use of health informatics MOOCs among students and instructors in Saudi Arabian academic institutions. The results of this study show that autonomy, relatedness, and competence must be considered in the design of health informatics MOOCs. CONCLUSIONS: A combination of these models can effectively explain the adoption and use of MOOCs in emerging fields such as health informatics.

Evaluation of two Massive Open Online Courses (MOOCs) in genomic variant interpretation for the NHS workforce.

BACKGROUND: The implementation of the National Genomic Medicine Service in the UK has increased patient access to germline genomic testing. Increased testing leads to more genetic diagnoses but does result in the identification of genomic variants of uncertain significance (VUS). The rigorous process of interpreting these variants requires multi-disciplinary, highly trained healthcare professionals (HCPs). To meet this training need, we designed two Massive Open Online Courses (MOOCs) for HCPs involved in germline genomic testing pathways: Fundamental Principles (FP) and Inherited Cancer Susceptibility (ICS). METHODS: An evaluation cohort of HCPs involved in genomic testing were recruited, with additional data also available from anonymous self-registered learners to both MOOCs. Pre- and post-course surveys and in-course quizzes were used to assess learner satisfaction, confidence and knowledge gained in variant interpretation. In addition, granular feedback was collected on the complexity of the MOOCs to iteratively improve the resources. RESULTS: A cohort of 92 genomics HCPs, including clinical scientists, and non-genomics clinicians (clinicians working in specialties outside of genomics) participated in the evaluation cohort. Between baseline and follow-up, total confidence scores improved by 38% (15.2/40.0) (95% confidence interval [CI] 12.4-18.0) for the FP MOOC and 54% (18.9/34.9) (95%CI 15.5-22.5) for the ICS MOOC (p < 0.0001 for both). Of those who completed the knowledge assessment through six summative variant classification quizzes (V1-6), a mean of 79% of respondents classified the variants such that correct clinical management would be undertaken (FP: V1 (73/90) 81% Likely Pathogenic/Pathogenic [LP/P]; V2 (55/78) 70% VUS; V3 (59/75) 79% LP/P; V4 (62/72) 86% LP/LP. ICS: V5 (66/91) 73% VUS; V6 (76/88) 86% LP/P). A non-statistically significant higher attrition rate was seen amongst the non-genomics workforce when compared to genomics specialists for both courses. More participants from the non-genomics workforce rated the material as "Too Complex" (FP n = 2/7 [29%], ICS n = 1/5 [20%]) when compared to the specialist genomics workforce (FP n = 1/43 [2%], ICS n = 0/35 [0%]). CONCLUSIONS: After completing one or both MOOCs, self-reported confidence in genomic variant interpretation significantly increased, and most respondents could correctly classify variants such that appropriate clinical management would be instigated. Genomics HCPs reported higher satisfaction with the level of content than the non-genomics clinicians. The MOOCs provided foundational knowledge and improved learner confidence, but should be adapted for different workforces to maximise the benefit for clinicians working in specialties outside of genetics.

Learner readiness for MOOCs in Omani higher education institutions: disparities between projections and reality.

This study investigates the level of readiness for massive open online courses (MOOCs) of students in Oman. It compares the readiness of ordinary students in the Omani higher education institutions (HEIs) and those outside HEIs who took a MOOC from the larger Omani society and tests for the differences between their levels of readiness. Additionally, it tests for the best predictor for future participation in MOOCs. In this study, readiness is defined as the possession of three sets of skills: technological, metacognitive, and motivational. A sequential two-phase research approach was used by first collecting data from 428 students in different HEIs and then collecting the same data from 253 non-HEI students from the general public who were offered and took a MOOC specifically designed for this study. While high levels of the three sets of skills were found in both study samples, the MOOC students were found to have significantly higher motivational and metacognitive skills than the higher education students. In this study, binary regression results indicate that comfort with eLearning is the best predictor for future participation in MOOCs. Given the high student readiness for MOOCs in Oman in this study, some recommendations are provided for higher education institutions to benefit from the fast-moving MOOC phenomenon.

Leveraging MOOCs for learners in economically disadvantaged regions.

While Massive Online Open Courses (MOOCs) have seen a surge in enrollments in higher education around the world especially during the Covid-19 pandemic, it is unclear if learners from the economically disadvantaged regions (EDR) are also able to capitalize on them. Specifically, challenges related to using MOOCs in these regions have been reported in the literature. Thus, the objective of this paper is to address the pedagogical challenge by investigating approaches to leverage MOOCs for learners in EDR. Drawing from the ARCS (i.e. Attention, Relevance, Confidence and Satisfaction) model, we proposed an embedded MOOCs approach where bite-sized MOOCs segments are integrated into in-class lectures under the guidance of the instructors. The effectiveness of the embedded MOOCs approach was evaluated and compared with other instructional methods. Results from randomized experiments showed that the embedded MOOCs approach had higher evaluations in terms of attention, relevance and satisfaction than face-to-face learning approach. In addition, the embedded MOOCs approach outperformed asynchronously blended MOOCs in enhancing students' relevance perception. Regression analysis further revealed that attention, confidence, and satisfaction perceptions were positively associated with students' intention to adopt the embedded MOOCs approach in their future studies. The findings shed light on how to utilize MOOCs and re-use content in MOOCs for global benefits and enable new pedagogical developments. The findings also underscore the importance of local social support and offline interactions to support the online learning materials.

Identifying learners' topical interests from social media content to enrich their course preferences in MOOCs using topic modeling and NLP techniques.

Interests play an essential role in the process of learning, thereby enriching learners 'interests will yield to an enhanced experience in MOOCs. Learners interact freely and spontaneously on social media through different forms of user-generated content which contain hidden information that reveals their real interests and preferences. In this paper, we aim to identify and extract the topical interest from the text content shared by learners on social media to enrich their course preferences in MOOCs. We apply NLP pipeline and topic modeling techniques to the textual feature using three well-known topic models: Latent Dirichlet Allocation, Latent Semantic Analysis, and BERTopic. The results of our experimentation have shown that BERTopic performed better on the scrapped dataset.

Students' continuance intention to use MOOCs: empirical evidence from India.

In recent years, there has been an increasing interest in understanding the Massive open online courses (MOOCs) due to its gaining popularity. Even though the number of online platforms and programs has grown during the COVID-19 pandemic, there is still a high rate of dropout and non-completion. In this work, the expectation-confirmation model is combined with MOOC features such as perceived openness, perceived reputation, and other factors i.e., perceived enjoyment, and perceived computer self-efficacy to investigate the learner's continued intention to use MOOC. A survey was undertaken and the data was collected from 383 students pursuing their degrees (undergraduate and post-graduate) in Karnataka state, India. The collected data were analyzed with structural equation modelling in Smart PLS 3. The study confirms a significant influence of confirmation and perceived usefulness on satisfaction, and direct significant influence of perceived computer self-efficacy, satisfaction, and perceived usefulness on continuance intention. Also, the results demonstrated the significant influence of confirmation on perceived enjoyment and usefulness and the effect of computer self-efficacy on usefulness. The findings in this study indicate that the MOOC platforms should focus on confirming learner expectations and the usefulness of courses to ensure student satisfaction and continuance of courses.

"Design and implementation challenges of massive open online course on research methods for Indian medical postgraduates and teachers -descriptive analysis of inaugural cycle".

BACKGROUND: In view of the growing popularity, reach and access for Massive Open Online Courses (MOOCs), India's apex body for medical education, the National Medical Commission (NMC) mandated uniform foundational course on research methods for the medical post graduates (PGs) and faculty members of the medical institutions under NMC as MOOC. This course is a pioneering effort in the field of India's PG medical education. NMC entrusted Indian Council of Medical Research (ICMR)-National Institute of Epidemiology (NIE) to design and offer the MOOC, named as Basic Course in Biomedical Research (BCBR). We describe the experience of designing and that of implementation challenges in the inaugural cycle of the course. METHODS: The course objective was to inculcate the fundamental concepts in research methods covering epidemiology and biostatistics in the form of video lectures, resource materials, discussion forum, assignments, feedback and a final proctored examination. The course was delivered over 16 weeks through MOOCs platform under the Indian Ministry of Education. We reviewed records, documents and faculty notes and described the course conceptualization, development, design and implementation process. We abstracted information from course portal on enrolment profile of the participants, self-reported course feedback (structured and open-ended on format, lectures and quality of contents), examination registration form, scores obtained in the assignments/examination and that of the participant queries. We described quantitative data using descriptive statistics. We presented the thematic analysis of qualitative data from open-ended questions in the feedback system and that of email interactions. RESULTS: The inaugural cycle (September-December 2019) was taken by 24,385 participants. Majority, 15,879 (65%) were from medical background. 13,242 (54%) were medical postgraduates and 2637 (11%) were medical teachers. Among the enrolled, 14,720 (60%) cleared the assignments. A total of 11,392 (47%), 8,205 (62%) medical PGs and 896 (34%) faculty members successfully completed the course. Feedback from 1305 (5%) participants had mean score of 4.5/5 (±0.7) for quality of teaching. We faced challenges in customizing the course for medical participants, unawareness among target group, digital illiteracy and the ongoing pandemic. CONCLUSIONS: During the inaugural cycle of the online Basic Course in Biomedical Research course, nearly half of the enrolled participants successfully completed and received the certificate. India's MOOC for enhancing research capabilities of future medical researchers encountered successes and challenges. Lessons learnt from the inaugural cycle will guide future directions and to address larger issues in terms of sustainability and replication by stakeholders in medical education in India or elsewhere.

Interest in Educational Data and Barriers to Data Use Among Massive Open Online Course Instructors.

Higher education instructors constantly rely on educational data to assess and evaluate the behavior of their students and to make informed decisions such as which content to focus on and how to best engage the students with it. Massive open online course (MOOC) platforms may assist in the data-driven instructional process, as they enable access to a wide range of educational data that is gathered automatically and continuously. Successful implementation of a data-driven instruction initiative depends highly on the support and acceptance of the instructors. Yet, our understanding of instructors' perspectives regarding the process of data-driven instruction, especially with reference to MOOC teaching, is still limited. Hence, this study was set to characterize MOOC instructors' interest in educational data and their perceived barriers to data use for decision-making. Taking a qualitative approach, data were collected via semi-structured interviews with higher education MOOC instructors from four public universities in Israel. Findings indicated that the instructors showed great interest mostly in data about social interactions between learners and about problems with the MOOC educational resources. The main reported barriers for using educational data for decision-making were lack of customized data, real-time access, data literacy, and institutional support. The results highlight the need to provide MOOC instructors with professional development opportunities for the proper use of educational data for skilled decision-making.

Looking at MOOC discussion data to uncover the relationship between discussion pacings, learners' cognitive presence and learning achievements.

The MOOCs (Massive Open Online Courses) forum carries rich discussion data that contains multi-level cognition-related behavior patterns, which brings the potential for an in-depth investigation into the development trend of the group and individual cognitive presence in discourse interaction. This paper describes a study conducted in the context of an introductory astronomy course on the Chinese MOOCs platform, examining the relationship between discussion pacings (i.e., instructor-paced or learner-paced discussion), cognitive presence, and learning achievements. Using content analysis, lag sequential analysis, logistic regression, and grouped regression approaches, the study analysed the online discussion data collected from the Astronomy Talk course involving 2603 participants who contributed 24,018 posts. The findings of the study demonstrated the significant cognitive sequential patterns, and revealed the significant differences in the distribution of cognitive presence with different discussion pacings and learning achievement groups, respectively. Moreover, we found that the high-achieving learners were mostly in the exploration, integration, and resolution phase, and learner-paced discussion had a greater moderating effect on the relationship between cognitive presence and learning achievements. Based on the findings and discussion, suggestions for improving the learners' cognitive presence and learning achievements in the MOOC environment are discussed.

Comprehensive evaluation of the use of technology in education - validation with a cohort of global open online learners.

Although a large variety of methodologies, contexts and perspectives have been used to examine educational application of technology, there is a paucity of instruments that are designed to comprehensively evaluate the use of technology in education. This paper presents a Confirmatory Factor Analysis (CFA) of an instrument that incorporates eight key dimensions: learning, affective, behavioral, technology, design, pedagogy, presence/community, and institutional environment. These dimensions were derived from rigorous systematic literature review and field specialist validation processes. The model was then refined and empirically confirmed in this study by 1,352 participants undertaking a Coursera open online course. The results of applying the instrument, as well as qualitative feedback from participants, are shared to illustrate its breadth and utility. The final 28 item "Comprehensive Evaluation of Use of Technology in Education" instrument is provided in full to support consistent, holistic and robust evaluation and comparison of technology use across educational contexts.

MOOC Behavior Analysis and Academic Performance Prediction Based on Entropy.

In recent years, massive open online courses (MOOCs) have received widespread attention owing to their flexibility and free access, which has attracted millions of online learners to participate in courses. With the wide application of MOOCs in educational institutions, a large amount of learners' log data exist in the MOOCs platform, and this lays a solid data foundation for exploring learners' online learning behaviors. Using data mining techniques to process these log data and then analyze the relationship between learner behavior and academic performance has become a hot topic of research. Firstly, this paper summarizes the commonly used predictive models in the relevant research fields. Based on the behavior log data of learners participating in 12 courses in MOOCs, an entropy-based indicator quantifying behavior change trends is proposed, which explores the relationships between behavior change trends and learners' academic performance. Next, we build a set of behavioral features, which further analyze the relationships between behaviors and academic performance. The results demonstrate that entropy has a certain correlation with the corresponding behavior, which can effectively represent the change trends of behavior. Finally, to verify the effectiveness and importance of the predictive features, we choose four benchmark models to predict learners' academic performance and compare them with the previous relevant research results. The results show that the proposed feature selection-based model can effectively identify the key features and obtain good prediction performance. Furthermore, our prediction results are better than the related studies in the performance prediction based on the same Xuetang MOOC platform, which demonstrates that the combination of the selected learner-related features (behavioral features + behavior entropy) can lead to a much better prediction performance.

Open to MOOCs? Evidence of their impact on labour market outcomes.

This paper investigates the effect that participation in massive open online courses (MOOCs) ecosystem can have on workers' labour market outcomes, mainly employment retaining. We use primary data collected between 2015 and 2017 and obtained from two surveys (pre-course and follow-up questionnaires) sent to participants in six MOOCs. The treatment group is composed of individuals participating in MOOCs in 2015 and the control group is composed of individuals who enrolled in MOOCs for the first time in 2017. Using a differences-in-differences approach, we find that participation in MOOCs can improve workers' employment retaining but not their wages. The positive effect on employment retaining is homogeneous in different geographical and economic areas and tends to be higher for individuals who have participated in more MOOCs in the past.

Killer Apps: Developing Novel Applications That Enhance Team Coordination, Communication, and Effectiveness.

As part of the Lorentz workshop, "Interdisciplinary Insights into Group and Team Dynamics," held in Leiden, Netherlands, this article describes how Geeks and Groupies (computer and social scientists) may benefit from interdisciplinary collaboration toward the development of killer apps in team contexts that are meaningful and challenging for both. First, we discuss interaction processes during team meetings as a research topic for both Groupies and Geeks. Second, we highlight teamwork in health care settings as an interdisciplinary research challenge. Third, we discuss how an automated solution for optimal team design could benefit team effectiveness and feed into team-based interventions. Fourth, we discuss team collaboration in massive open online courses as a challenge for both Geeks and Groupies. We argue for the necessary integration of social and computational research insights and approaches. In the hope of inspiring future interdisciplinary collaborations, we develop criteria for evaluating killer apps-including the four proposed here-and discuss future research challenges and opportunities that potentially derive from these developments.

Navigating the changing learning landscape: perspective from bioinformatics.ca.

With the advent of YouTube channels in bioinformatics, open platforms for problem solving in bioinformatics, active web forums in computing analyses and online resources for learning to code or use a bioinformatics tool, the more traditional continuing education bioinformatics training programs have had to adapt. Bioinformatics training programs that solely rely on traditional didactic methods are being superseded by these newer resources. Yet such face-to-face instruction is still invaluable in the learning continuum. Bioinformatics.ca, which hosts the Canadian Bioinformatics Workshops, has blended more traditional learning styles with current online and social learning styles. Here we share our growing experiences over the past 12 years and look toward what the future holds for bioinformatics training programs.

The Involvement of Academic and Emotional Support for Sustainable Use of MOOCs.

MOOCs, the Massive Open Online Courses, are online educational courses that offer open access to a large number of participants globally. However, online engagement during MOOC learning remains a problem, as reflected in relatively high dropout rates. This paper involves academic and emotional support, aiming to explore whether they contribute to users' sustainable use of the MOOC platform. A total of 410 college students learning English as a foreign language (EFL) and with MOOC learning experience participated in this study. Employing the structural equation modeling (SEM) techniques, we examined the relationships among five factors in the EFL MOOC learning context: academic support (AS), emotional support (ES), perceived usefulness (PU), perceived ease of use (PEoU), and platform reputation (PR). The results indicate that academic support influences learners' perceptions of the usefulness and ease of use of the MOOC platform, as well as enhancing learners' feelings of being emotionally supported. Simultaneously, platform reputation plays a crucial role in influencing learners' perceptions of MOOC platforms. However, results suggest that emotional support does not have a statistically significant impact on the perceived usefulness and perceived ease of use of the platform in EFL MOOC learning contexts.

Exploring HTML5 Package Interactive Content in Supporting Learning Through Self-Paced Massive Open Online Courses on Healthy Aging: Mixed Methods Study.

BACKGROUND: The rapidly aging population and the growth of geriatric medicine in the field of internal medicine are not supported by sufficient gerontological training in many health care disciplines. There is rising awareness about the education and training needed to adequately prepare health care professionals to address the needs of the older adult population. Massive open online courses (MOOCs) might be the best alternative method of learning delivery in this context. However, the diversity of MOOC participants poses a challenge for MOOC providers to innovate in developing learning content that suits the needs and characters of participants. OBJECTIVE: The primary outcome of this study was to explore students' perceptions and acceptance of HTML5 package (H5P) interactive content in self-paced MOOCs and its association with students' characteristics and experience in using MOOCs. METHODS: This study used a cross-sectional design, combining qualitative and quantitative approaches. Participants, predominantly general practitioners from various regions of Indonesia with diverse educational backgrounds and age groups, completed pretests, engaged with H5P interactive content, and participated in forum discussions and posttests. Data were retrieved from the online questionnaire attached to a selected MOOC course. Students' perceptions and acceptance of H5P interactive content were rated on a 6-point Likert scale from 1 (strongly disagree) to 6 (strongly agree). Data were analyzed using SPSS (IBM Corp) to examine demographics, computer literacy, acceptance, and perceptions of H5P interactive content. Quantitative analysis explored correlations, while qualitative analysis identified recurring themes from open-ended survey responses to determine students' perceptions. RESULTS: In total, 184 MOOC participants agreed to participate in the study. Students demonstrated positive perceptions and a high level of acceptance of integrating H5P interactive content within the self-paced MOOC. Analysis of mean (SD) value across all responses consistently revealed favorable scores (greater than 5), ranging from 5.18 (SD 0.861) to 5.45 (SD 0.659) and 5.28 (SD 0.728) to 5.52 (SD 0.627), respectively. This finding underscores widespread satisfaction and robust acceptance of H5P interactive content. Students found the H5P interactive content more satisfying and fun, easier to understand, more effective, and more helpful in improving learning outcomes than material in the form of common documents and learning videos. There is a significant correlation between computer literacy, students' acceptance, and students' perceptions. CONCLUSIONS: Students from various backgrounds showed a high level of acceptance and positive perceptions of leveraging H5P interactive content in the self-paced MOOC. The findings suggest potential new uses of H5P interactive content in MOOCs, such as interactive videos with pop-up questions, to substitute for synchronous learning. The study underscores the significance of tailored educational strategies in supporting the professional development of health care professionals.

Examining Factors That Influence Learner Retention in MOOCs During the COVID-19 Pandemic Time.

Massive Open Online Courses have become a frequent platform for learners to acquire knowledge. This study aims to explore multiple factors influencing learner retention in MOOCs during the COVID-19 pandemic. To address this, we collected quantitative and qualitative data from questionnaires and qualitative data from interviews and then analyzed them through the Partial Least Square-Structural Equation Modeling to test 14 research hypotheses. The proposed research model and research hypotheses are empirically tested with 243 participants across the world. According to the results, support is found for all of the 14 research hypotheses. We confirmed 14 factors influencing learner retention in MOOCs. The result is beneficial for designers and manufacturers of MOOCs to improve the quality of the products and facilitate online or blended learning during this special time. It could also help students improve their learning experiences. Future research could examine influencing factors of learner retention in MOOCs with interdisciplinary cooperation.

Motivational Understanding of MOOC Learning: The Impacts of Technology Fit and Subjective Norms.

This study examines the mechanisms underlying the relationship between motivation and massive open online course (MOOC) learning intention, and the contextual moderators that affect this mechanism. Drawing on motivational theory and the related literature, this study investigates how motivation affects students' intention to learn with MOOCs and the related meditation and moderation effects. The findings of our study show that both extrinsic and intrinsic motivations have a significant influence on intention to learn with MOOCs. In addition, the results also suggest that the relationship between extrinsic motivation and intention to learn is mediated by the technology fit perceived by learners but not the relationship between intrinsic motivation and intention to learn. Furthermore, the relationships between both extrinsic and intrinsic motivation and intention to learn are moderated by subjective norms. This study enriches the extant literature on the impact of technology fit and subjective norms on MOOC learning. Few studies have focused on how students can be effectively encouraged to take MOOCs. Given the lack of theoretical and empirical research, this study developed a theoretical model and conducted an empirical study to fill the research gap.

Using Learner Reviews to Inform Instructional Video Design in MOOCs.

Videos are arguably the most important and frequently used instructional resource in massive open online courses (MOOCs). Recent research has explored learners' perceptions and preferences regarding MOOC instructional videos. However, these studies are often limited to a small number of specific courses, and few grounded theory studies have been undertaken to investigate this topic. In the present study, a multiple-coder research methodology was adopted to analyze 4534 learner reviews of MOOCs in 14 categories. The study aimed to identify key characteristics associated with learners' favorable perceptions of MOOC videos, types of supplemental or in-video resources learners perceive helpful to support MOOC video use, and video production features learners value. Results revealed that (a) "organized", "detailed", "comprehensible", "interesting", and "practical" were the top five important characteristics associated with learners' favorable perceptions of MOOC videos; (b) learners perceived "presentation slides", "reading materials", "post-video assessments", "embedded questions", and "case studies" as helpful resources to support their utilization of MOOC videos; and (c) learners found "duration" a more salient production feature than "editing", "resolution", "subtitles", "music", or "voice". The findings present implications for MOOC video design and foundations for future research avenues.