MOOC: tsunami, revolution or fad? Lorenzo García Aretio
Revista iberoamericana de educación a distancia,
01/2015, Volume:
18, Issue:
1
Journal Article
Peer reviewed
Open access
There are millions of people in the world who have followed some kind of MOOC (Massive Open Online Course) to date. There are hundreds of thousands who are currently enrolled in some of these ...courses. We can be more or less critics with MOOC, however by the effects that were producing before, it would not be total nonsense the tsunami term, that Brooks (2012) used in a New York Times article (3-5-2012) to qualify these massive, open and online courses.
Due to a large number of massive open online courses (MOOC), it becomes more and more difficult for the users to determine which course best suits their needs. To improve the efficiency of course ...selection, a place is needed where they can visually compare the offers of different MOOC providers. The article aims to identify the number and characteristics of massive open online courses for language learning (MOOLC) using MOOC aggregators and to trace their impact on the development of language education. The article presents different approaches to such concepts as MOOC, MOOLC, MOOC platform, MOOC aggregator and MOOC provider. The article determines MOOC aggregators, which would allow identifying the number and characteristics of MOOLC, and examines the possibilities of some MOOC platforms, which offer courses for English language learning, basing on the selected criteria for evaluation of the existing MOOC platforms. The author concludes that nowadays, the ideal MOOC platform, which could offer the necessary conditions for creating an ideal MOOLC, does not exist.
This mixed methods study explores instructor motivations for offering massive open online courses (MOOCs) as well as the instructional innovations used to enhance the MOOC design. The researchers ...surveyed 143 MOOC instructors worldwide and then interviewed 12 of these instructors via Zoom. They also extensively reviewed the MOOCs of the interviewees. The primary motivations for offering MOOCs included “growth” needs such as curiosity about MOOCs and the exploration of new ways of teaching. In addition, “relatedness” needs of instructors included reaching more people, showcasing research and teaching, marketing their university, integrating interactive technology, and obtaining peer reviews. The perceived instructional innovations of these MOOC instructors included using problem-based learning, service learning in MOOCs, and shortening the length of videos. Overall, these MOOC instructors were satisfied with their MOOC designs.Cette étude faisant appel à des méthodes mixtes explore les motivations des instructeurs de cours en ligne ouverts à tous ainsi que les innovations pédagogiques utilisées pour améliorer la conception de ces cours. Les chercheurs ont procédé au sondage de 143 instructeurs de cours en ligne ouverts à tous à travers le monde et ont ensuite interviewé 12 de ces instructeurs par l’entremise de Zoom. Ils ont également réalisé un examen approfondi des cours en ligne ouverts à tous des instructeurs interviewés. Les motivations principales pour l’offre de cours en ligne ouverts à tous comprenaient des besoins relatifs à la « croissance », comme la curiosité au sujet de ces cours et l’exploration de nouvelles façons d’enseigner. De plus, les désirs relationnels des instructeurs comprenaient joindre plus de gens, mettre en lumière la recherche et l’enseignement, publiciser leur université, intégrer la technologie interactive et obtenir des évaluations par les pairs. Les innovations pédagogiques perçues par ces instructeurs de cours en ligne ouverts à tous comprenaient l’utilisation de l’apprentissage par résolution de problèmes, de l’apprentissage par le service dans les cours en ligne ouverts à tous et la durée écourtée des vidéos. Dans l’ensemble, les instructeurs de cours en ligne ouverts à tous étaient satisfaits de leur conception de cours.
The high dropout rate from Massive Open Online Courses (MOOCs) has been a major concern of researchers and educators over the years. Although academic papers on MOOCs have mushroomed over the past ...ten years, few studies have focused on MOOC dropout and retention. In particular, research on hospitality and tourism MOOCs has remained nascent despite the field's significant contribution to international business and global employment. Because of the lack of relevant literature on hospitality and tourism MOOCs, this study conducts a systematic review of the MOOC literature on the broader education field, examining the MOOC dropout phenomenon and retention strategies. The results of a content analysis based on journal articles' main research topic show four clusters: prediction, continuance intention, motivation, and attrition. Thematic analysis is used to categorize the dropout factors into seven major themes: learning experience, interactivity, course design, technology, language, time, and situation. This paper concludes with a summary of the results, recommendations, practical implications, limitations, and directions for future research.
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BFBNIB, NUK, PILJ, SAZU, UL, UM, UPUK
Massive open online courses (MOOCs), contribute significantly to individual empowerment because they can help people learn about a wide range of topics. To realize the full potential of MOOCs, we ...need to understand their factors of success, here defined as the use, user satisfaction, along the individual and organizational performance resulting from the user involvement. We propose a theoretical framework to identify the determinants of successful MOOCs, and empirically measure these factors in a real MOOC context. We put forward the role of gamification and suggest that, together with information system (IS) theory, gamification proved to play a crucial role in the success of MOOCs.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Massive Open Online Courses (MOOC) is a new phenomenon in online learning that has aroused increasing interest by researchers as a significant contribution to improving educational system quality and ...openness. The purpose of this paper is to compile and analyze MOOC research that has been published between 2012 and 2016. A systematic analysis technique was employed and Template Analysis (TA) approach was used for mapping MOOC research into three dimensions in accordance with the Biggs 3P model. First dimension is Presage, include the following factors: Learners’ characteristics with sub-factors (learner demographics, learner motivation, and interactivity) and instructor. Second, Process, including factors of pedagogy, pattern of engagement, instructional design, assessment, credit, plagiarism, sustainability, and learning analytics. Third dimension is Product, including factors of student dropout rate and MOOC quality. This classification is aimed at providing a comprehensive overview for readers interested in MOOCs who seek to understand the critical success factors influencing MOOC success.
This study aimed to understand the psychological processes underlying learners’ continuance intention to participate in massive open online courses (MOOCs). We proposed a research model incorporating ...three variables that are well-explored in the relevant literature, namely satisfaction, attitude and confirmation, and two rarely examined variables, namely perceived MOOC performance and habit. Two studies were conducted with Chinese MOOC learners using multiple data sources, specifically open online textual data, focus group interviews and questionnaire surveys. Our research revealed that perceptions of MOOC performance were represented by two attribute-level qualities, knowledge transmission quality and interaction quality. Interaction quality was not related to satisfaction with the learning experience, whereas a habit of choosing MOOCs as a learning mode was found to significantly increase continuance intention. The insights from this study can help guide MOOC instructors to improve the learner experience in this virtual environment, MOOC providers to maintain the sustainability of MOOCs and universities to prepare MOOCs for inclusion in blended classes.
•Perceptions of MOOC performance were represented by two attribute-level qualities.•Reliable measurement scales for MOOC performance were developed and validated.•Interaction quality was not related to satisfaction with the learning experience.•Habit was found to be a significant determinant of continuance intention.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Predicting student performance is a major tool in learning analytics. This study aims to identify how different measures of massive open online course (MOOC) data can be used to identify points of ...improvement in MOOCs. In the context of MOOCs, student performance is often defined as course completion. However, students could have other learning objectives than MOOC completion. Therefore, we define student performance as obtaining personal learning objective(s). This study examines a subsample of students in a graduate‐level blended MOOC who shared on‐campus course completion as a learning objective. Aggregated activity frequencies, specific course item frequencies, and order of activities were analysed to predict student performance using correlations, multiple regressions, and process mining. All aggregated MOOC activity frequencies related positively to on‐campus exam grade. However, this relation is less clear when controlling for past performance. In total, 65% of the specific course items showed significant correlations with final exam grade. Students who passed the course spread their learning over more days compared with students who failed. Little difference was found in the order of activities within the MOOC between students who passed and who failed. The results are combined with course evaluations to identify points of improvement within the MOOC.
Lay Description
What is currently known about the subject?
Learning analytics focuses on the analysis of learner data to improve learning and teaching.
Several studies tried to predict MOOC completion using general frequencies of activities.
It is typically found that being active in an MOOC has a positive effect on student performance.
It is still hard to translate student performance predictions into actionable feedback.
What does this paper add?
First step from descriptive learning analytics towards more explanatory learning analytics.
It is more insightful to define student performance in MOOCs as obtaining personal learning objective(s).
Analysis of order of activities in MOOCs is useful next to frequencies of activities to predict student performance.
Students who passed spread their learning over more days compared with students who failed.
Analysis of specific course items can be used to identify points of improvement in the MOOC.
What does this mean for practitioners?
MOOCs can be used for blended learning.
Learning analytics on MOOC data can be used for course improvements.
Course evaluations are useful to interpret the results from learning analytics.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Massive Open Online Courses (MOOCs) have received much attention in higher education; however, evidence about MOOCs at the K-12 level is scarce. To shed light on the phenomenon, we use the i-MOOC ...that aims at fostering upper secondary level students’ information literacy. The i-MOOC is a blended MOOC developed and refined in a design research process; it meets established criteria for high-quality MOOCs. In 2020, 1032 upper secondary level students in German-speaking Switzerland took the i-MOOC; the sample comprises N = 167 students who voluntarily filled in a questionnaire. The students are mainly from high schools and vocational schools. Learning effects are captured with a performance test. Information literacy gains are significant and medium in size: d = 0.75. The technology acceptance of students is evaluated using the extended unified theory of acceptance and use of technology (UTAUT2). Student technology acceptance of K-12 MOOCs is primarily driven by hedonic motivation, i.e., perceived fun and entertainment. However, this type of motivation negatively predicts learning gains. Implications for teachers and educational decision makers are discussed.
•A systematic literature review on empirical evidence for K-12 MOOCs.•A conceptual framework for the quantitative evaluation of K-12 MOOCs.•Empirical evidence for a K-12 MOOC at upper secondary level in Switzerland.•Based on our evidence, the validity of student evaluation of K-12 MOOCs is doubtful.•Based on our evidence, hedonic motivation is a negative predictor for learning gain.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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