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«Implicaciones de datos de aprendizaje procedentes de MOOCs», por Edmundo Tovar Caro, profesor titular de la UPM

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23_11_2018 Seminario eMadrid sobre «Analíticas para el aprendizaje» organizado por la UAM

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«Implicaciones de datos de aprendizaje procedentes de MOOCs», por Edmundo Tovar Caro, profesor titular de la UPM

  1. 1. Implicaciones de datos de aprendizaje procedentes de MOOCs Seminario eMadrid sobre «Analíticas para el aprendizaje Madrid, 23 de noviembre de 2018 Edmundo Tovar Caro etovar@fi.upm.es Universidad Politécnica de Madrid
  2. 2. Learning Analytics (LA). Processes Mohammad Khalil & Martin Ebner, TU Graz
  3. 3. The Environment MOOCs and Open Education
  4. 4. A way of carrying out education, often using digital technologies. Its aim is to widen access and participation to everyone by removing barriers and making learning accessible, abundant, and customisable for all. It offers multiple ways of teaching and learning, building and sharing knowledge. It also provides a variety of access routes to formal and non-formal education, and connects the two Open Education is seen as Source: JRC IPTS Report: Opening up Education: a support framework for higher education institutions. http://publications.jrc.ec.europa.eu/repository/handle/JRC101436 Open Education CC BY Jonatan Castaño Muñoz Jornada red.es-UC3 sobre formación digital con tecnología abierta
  5. 5. Research Lines MOOCs and Open Education Who enrolls? Impact on Higher Education How is the learning?
  6. 6. New measurements needed — Different audiences than traditional HE degrees — Different intentions and motivations Source: online course report State of the MOOC 2016: A Year of Massive Landscape Change For Massive Open Online Courses CC BY Jonatan Castaño Muñoz Jornada red.es-UC3 sobre formación digital con tecnología abiert
  7. 7. For whom? — Main actors in this scenario: MOOCs providers and EC — To develop policy guidelines: issues to learn more about the population of MOOC learners — Benchmarking: reports will provide MOOC providers insigths about their MOOCs compared with other MOOCs
  8. 8. New measurements needed
  9. 9. Research Lines MOOCs and Open Education Who enrolls?
  10. 10. Profiles of MOOC participants ü MOOC format is characterized by the great diversity of enrolled people ü There is a lack of knowledge of participants’ background ü It is needed to provide a real picture of the heterogeneity of MOOC participants
  11. 11. — Geographic distribution — There are students from 117 countries. The country with more students is USA with 17.4% of the total, followed by Spain (6.9%) and India (6.8%). 1st MOOC of the IEEE Education Society edX analytics
  12. 12. — MOOCKnowledge online pre-questionnaire — Sociodemographics: — gender, date of birth, socioeconomic status (highest degree or level of school completed, employment status (currently and two years ago)). — Previous experiences with MOOCs: — MOOCs related to participants’ current job, number of completed MOOC with certification and kind of certificates obtained. — Usefulness of the MOOC: — professional, personal and academic life. Data set
  13. 13. — The scenario is fairly uniform in the period of two years until the start of the course. — Participants with a job are almost three quarters of the dataset in both periods of time Sociodemographics. Employment status (currently and two years ago) PROFESSIONAL STATUS Professional status Time window current (%) 2 years ago (%) Employed 102 (73%) 102 (76.7%) self-employed 12 (8.6%) 11 (8.3%) unemployed and looking for a job 9 (6.4%) 2 (1.5%) unemployed but not currently looking for a job 1 (0.7%) 0 a student (not in the labour force) 8 (5.7%) 12 (9%) in retirement or early retirement 6 (4.3%) 4 (3%) permanently disabled 1 (0.7%) 0 a home maker (fulfilling domestic tasks) 1 (0.7%) 2 (1.5%) TOTAL 140 133
  14. 14. — Most of them are aware of the MOOC’s usefulness on their professional sphere Goals and intentions. Usefulness of the MOOC for the participants’ professional, personal and academic life Usefulness of the MOOC for the professional, personal and academic life of the participants (n = 119))
  15. 15. Extended profiles of MOOC participants — ANALYSIS: Approach 1: Data mining
  16. 16. Study case — Scenario: — Analysis of the behavior of students attending the different levels of involvement to the MOOC who have registered — Groups of interest: managers in open education, academic staff of MOOCs,… — Objective: — To increase the size of the target cluster in next editions of the MOOC — Phases: — 1. Clustering of participants — 2. Target cluster? — 3. Identifying profile of students “bridge” between the target cluster and other clusters — 4. Promoting the participation of “bridge” students in the future — ANALYSIS: Approach 2: SNA
  17. 17. Study case. Clustering of groups of participants — The SNA analysis is based on the similarity of participant profiles: if two participants give the same answer to a question, a relationship exists between them. — The network consists of 316 nodes (participants) with 42117 relationships pointing. — We obtained three clusters represented with different colors. — Each cluster represents the pattern of participants that have the tendency to answer of the same way. HOW? SNA metrics and filters: • Weight (link) Clustering: modularity metric method After applying multiple filters to the network the number of nodes is reduced to 306 and the number of edges to 23216.
  18. 18. Research Lines MOOCs and Open Education Impact on Higher Education
  19. 19. Creating a SPOC from an OCW in Higher Education — Improvements in the student perceptions of materials and resources — The elimination of the final exam. Assessments in peer-to-peer format and applied rubrics for assessment. — Short videos and answer questionnaires, instead of attending long traditional classes.
  20. 20. Research Lines MOOCs and Open Education How is the learning?
  21. 21. The influence of different teaching modes on learner s learning behaviors — In pure MOOCs — In flipped clasroom modes — In traditional classroom
  22. 22. Thank you! Edmundo Tovar Caro (etovar@fi.upm.es)
  23. 23. MOOCKnowledge project Initiative launched by the Institute of Prospective Technological Studies (IPTS). Executed by the Open University of the Netherlands (OUNL) in cooperation with the Open University of Catalonia (UOC) and Universidad Politécnica de Madrid (UPM) MOOCKnowledge pursues to assess the current perspective of learners as participants of European MOOCs: when, why and how the participants enrolled in one or more MOOCs take advantage of them Goal: building a [large scale] and cross-provider data collection based on the experiences reported by the participants of the MOOCs offered by providers that collaborate with the project with the intention of a more deepen understanding of issues related to MOOC format Online multilingual survey: • Pre-questionnaire • Post-questionnaire • Follow-up questionnaire Pre-questionnaire: • attibutes: demographics, linguistics, motivation, intentions, LLL, MOOC experience, prior satisfaction of participants with MOOC format
  24. 24. Clustering
  25. 25. Clustering
  26. 26. Analysis Approach 1: Data mining
  27. 27. Integrated regulation: tendency to try new things, to keep up to date, aligned with training needs Identified regulation: contribution of value, considered useful, meaningful and beneficial Extrinsic regulation: avoid feelings of ashamed of myself or guilt Amotivation: no desire to do the MOOC, it is considered a waste of time, no priority for the participant and he/she would prefer to do other things Extended profiles of MOOC participants Motivational perspective Introjected regulation: behavior to avoid guilt or to enhance the ego
  28. 28. The features that make up the degree of prior satisfaction of participants are … • course materials • MOOC presentation • video lecture • MOOC website • teacher(s) • communication with organizers of the MOOC • learning activities • discussions in the MOOCs forum • assignments • quizzes • feedback given to participants • pace of the MOOC • language used • difficulty level of the MOOC • needed technical requirements • offered certifications options Prior satisfaction perspective Extended profiles of MOOC participants
  29. 29. Satisfied (790 participants) Indifferent (405 participants) Dissatisfied (50 participants) MOOC presentation (0,941) Language used (0,934) Course materials (0,920) Learning activities (0,909) Technical requirements (0,906) MOOC website (0,885) Teacher(s) (0,880) Video lecture (0,866) MOOC level (0,856) Assignments (0,837) MOOC pace (0,792) Quizzes (0,768) Communication organizers (0,719) Feedback given (0,680) Certification options (0,642) Forum discussions (0,573) Assignments (0,815) Feedback given (0,807) MOOC pace (0,783) Quizzes (0,775) MOOC level (0,738) Certification options (0,723) Learning activities (0,711) Teacher(s) (0,709) Forum discussions (0,709) Communication organizers (0,689) Technical requirements (0,662) MOOC website (0,657) Video lecture (0,652) Course materials (0,644) MOOC presentation (0,635) Language used (0,627) Course materials (0,800) MOOC presentation (0,800) Assignments (0,780) Quizzes (0,780) MOOC level (0,780) Video lecture (0,780) MOOC website (0,780) Language used (0,760) Feedback given (0,740) Technical requirements (0,740) Teacher(s) (0,720) MOOC pace (0,700) Communication organizers (0,700) Learning activities (0,700) Certification options (0,680) Forum discussions (0,573) Preliminary findings: prior satisfaction + No Experience with MOOC format (337 participants)
  30. 30. 74 participants with high languages proficiency, reasonable motivation before their enrollment in a new course, and without previous experience in MOOC format 214 211 212 Preliminary findings: extended profiles 104 participants with high languages proficiency, reasonable motivation before their enrollment in a new course, and a high degree of previous satisfaction in MOOC format 53 participants with high languages proficiency, reasonable motivation before their enrollment in a new course, and indifference regarding MOOC format
  31. 31. Analysis Approach 2: SNA PhD Student: Jorge López
  32. 32. Exploration of SNA to the Moocknowledge data — An initial study has been conducted on the potential of social network analysis (SNA) and its metrics for: — Analyzing data obtained from the answers the participants. — Exploring useful scenarios. — The data source used comes from 715 participants of the MOOC on Test Anxiety Management.
  33. 33. Study case. 1. Clustering of groups of participants — Cluster 1 (Green color): Students always finish the MOOC including all the assignements and assessments — Cluster 2 (Red color): There is diversity of levels of involvement in its members — Cluster 3 (Blue color): Students finish the MOOC very often doing all the activities planned
  34. 34. Study case. 2. Target cluster? — Supossed: — Target cluster is number 2 — Objective: — In future editions of the MOOC we seek to increase the target cluster size, preserving its characteristics, through the participation of cluster 1.
  35. 35. Study case. 3. Identifying profile of students “bridge” — Profile of students contributing to the objective — Second stage of tertiary education — Employed for wages — Woman — Spanish — Born in the 1960s — Living together with partner — Working in the Public administration and defense; compulsory social security sector HOW? SNA metrics and filters: Betweenness

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