Learning in the opennessthe lost way of the MOOC

Referències bibliogràfiques

• Álvarez, C., & San Fabián, J. L. (2012). La elección del estudio de caso en investigación educativa. Gazeta de Antropología, 28(1), 1–13.
• Batchelor, J., & Lautenbach, G. (2015). Cultivating lifelong learning: Pre-service teachers and their MOOCs. 2015 IST-Africa Conference, IST-Africa 2015, (pp. 1–8). https:// doi.org/10.1109/ISTAFRICA.2015.7190557
• Bolívar, C. R. (2008). El enfoque multimétodo en la investigación social y educativa: Una mirada desde el paradigma de la complejidad. Teré: Revista de Filosofía y SocioPolítica de La Educación, 4(8), 13–28.
• Boude, O., & Medina, A. (2011). Desarrollo de competencias a través de un ambiente de aprendizaje mediado por TIC en educación superior. Educación Médica Superior, 25(3), 301–311.
• Conole, G. (2016). MOOCs as disruptive technologies: Strategies for enhancing the learner experience and quality of MOOCs. Revista de Educación a Distancia (RED), 50(2), 1– 18. http://dx.doi.org/10.6018/red/50/2
• Creswell, J. W. (2009). Research design: Qualitative, quantitative, and mixed methods approaches (Third edition). Sage publications.
• Cross, S., & Whitelock, D. (2017). Similarity and difference in fee-paying and no-fee learner expectations, interaction and reaction to learning in a massive open online course. In terac tive Learning Environmen ts, 25(4) , 439–451 . h t tps://doi .org/ 10.1080/10494820.2016.1138312
• Dessì, D., Fenu, G., Marras, M., & Reforgiato, D. (2019). Bridging learning analytics and Cognitive Computing for Big Data classification in micro-learning video collections. Computers in Human Behavior, 92, 468–477. https://doi.org/10.1016/ j.chb.2018.03.004
• Díaz, S. M. (2014). Los métodos mixtos de investigación: Presupuestos generales y aportes a la evaluación educativa. Revista Portuguesa de Pedagogía, 48(1), 7–23. https:// doi.org/10.14195/1647-8614_48-1_1
• Duart, J. M., Roig-Vila, R., Mengual, S., & Maseda, M.Á. (2017). La calidad pedagógica de los MOOC a partir de la revisión sistemática de las publicaciones JCR y Scopus (2013-2015). Revista Española de Pedagogía, 75(1), 29–46. https://doi.org/ 10.22550/REP75-1-2017-02
• Grant, M. J., Button, C. M., & Snook, B. (2017). An Evaluation of Interrater Reliability Measures on Binary Tasks Using d-Prime. Applied Psychological Measurement, 41(4), 264–276. https://doi.org/10.1177/0146621616684584
• Hermans, R., Tondeur, J., van Braak, J., & Valcke, M. (2008). The impact of primary school teachers’ educational beliefs on the classroom use of computers. Computers & Education, 51(4), 1499–1509. https://doi.org/10.1016/j.compedu.2008.02.001
• Higashi, R. M., Schunn, C. D., & Flot, J. B. (2017). Different underlying motivations and abilities predict student versus teacher persistence in an online course. Educational Technology Research and Development, 65, 1471–1493. https://doi.org/10.1007/ s11423-017-9528-z
• Houghton, C., Casey, D., Shaw, D., & Murphy, K. (2013). Rigour in qualitative case-study research . Nurse Researcher, 20(4) , 12–17 . https://doi.org/10 .7748/ nr2013.03.20.4.12.e326
• Hsu, S. (2017). Developing and validating a scale for measuring changes in teachers’ ICT integration proficiency over time. Computers & Education, 111, 18–30. https:// doi.org/10.1016/j.compedu.2017.04.001
• Jin, D., Shi, S., Zhang, Y., Abbas, H., & Goh, T.-T. (2019). A complex event processing framework for an adaptive language learning system. Future Generation Computer Systems, 92, 857–867. https://doi.org/10.1016/j.future.2017.12.032
• Kashyap, A., & Nayak, A. (2018). Different Machine Learning Models to Predict Dropouts in MOOCs. 2018 International Conference on Advances in Computing, Communications and Informatics ( ICACCI) , ( pp . 80 – 8 5 ) . https://doi.org /10.109 / ICACCI.2018.8554547
• Khalil, M., & Ebner, M. (2016). When Learning Analytics Meets MOOCs—A Review on iMooX Case Studies. In G. Fahrnberger, G. Eichler, & C. Erfurth (Eds.), Innovations for Community Services (Vol. 648, pp. 3–19). Springer International Publishing. https:// doi.org/10.1007/978-3-319-49466-1_1
• Khan, Md. S. H., & Markauskaite, L. (2017). Approaches to ICT-enhanced teaching in technical and vocational education: A phenomenographic perspective. Higher Education, 73(5), 691–707. https://doi.org/10.1007/s10734-016-9990-2
• Lemos de Carvalho, G., & Raposo, M. (2017). Análisis de la perspectiva pedagógica de los MOOC ofertados en lengua portuguesa. Revista Española de Pedagogía, 75(1), 101– 119. https://doi.org/10.22550/REP75-1-2017-06
• Lerís, D., Sein-Echaluce, M. L., Hernández, M., & Bueno, C. (2017). Validation of indicators for implementing an adaptive platform for MOOCs. Computers in Human Behavior, 72, 783–795. https://doi.org/10.1016/j.chb.2016.07.054
• Li, K. (2019). MOOC learners’ demographics, self-regulated learning strategy, perceived learning and satisfaction: A structural equation modeling approach. Computers & Education, 132, 16–30. https://doi.org/10.1016/j.compedu.2019.01.003
• Li, W., Gao, M., Li, H., Xiong, Q., Wen, J., & Wu, Z. (2016). Dropout prediction in MOOCs using behavior features and multi-view semi-supervised learning. 2016 International Joint Conference on Neural Networks (IJCNN), (pp. 3130–3137). https://doi.org/ 10.1109/IJCNN.2016.7727598
• Mackness, J., Waite, M., Roberts, G., & Lovegrove, E. (2013). Learning in a small, task– oriented, connectivist MOOC: Pedagogical issues and implications for higher education. The International Review of Research in Open and Distributed Learning, 14(4). https://doi.org/10.19173/irrodl.v14i4.1548
• Matías, H., & Pérez, A. (2014). Los Cursos en Línea Masivos y Abiertos (MOOC) como alternativa para la educación a distancia (Massive Open Online Courses (MOOC), an alternative to distance learning). GECONTEC: Revista Internacional de Gestión Del Conocimiento y La Tecnología, 2(2), 1–9.
• Mertens, D. M. (2014). Research and evaluation in education and psychology: Integrating diversity with quantitative, qualitative, and mixed methods. Sage publications.
• Nagrecha, S., Dillon, J. Z., & Chawla, N. V. (2017). MOOC Dropout Prediction: Lessons Learned from Making Pipelines Interpretable. Proceedings of the 26th International Conference on World Wide Web Companion - WWW ’17 Companion, (pp. 351–359). https://doi.org/10.1145/3041021.3054162
• Ossiannilsson, E., Altinay, F., & Altinay, Z. (2015). Analysis of MOOCs practices from the perspective of learner experiences and quality culture. Educational Media International, 52(4), 272–283. https://doi.org/10.1080/09523987.2015.1125985
• Pazur, K., Divjak, B., & Arbanas, K. (2016). Preparing ICT Graduates for Real-World Challenges: Results of a Meta-Analysis. IEEE Transactions on Education, 1–7. https://doi.org/10.1109/TE.2016.2633959
• Pete, J., Mulder, F., & Oliveira, J. D. (2017). Differentiation in Access to, and the Use and Sharing of (Open) Educational Resources among Students and Lecturers at Kenyan Universities. Open Praxis, 9(2), 173. https://doi.org/10.5944/openpraxis.9.2.574
• Pilli, O., & Admiraal, W. (2016). A taxonomy for Massive Open Online Courses. Contemporary Educational Technology, 7(3), 223–240.
• Ramírez, M. S. (2013). Challenges and perspectives for the open education movement in the distance education environment: A diagnostic study in a SINED project. RUSC. Universities and Knowledge Society Journal, 10(2), 170. https://doi.org/10.7238/ rusc.v10i2.1719
• Ramírez, M. S., & García-Peñalvo, F. J. (2015). Movimiento educativo abierto. Virtualis, 6(12), 1–13.
• Raposo, M., Martínez, E., & Sarmiento, J. A. (2015). A Study on the Pedagogical Components of Massive Online Courses. Comunicar, 22(44), 27–35. https://doi.org/10.3916/ C44-2015-03
• Robles, P., & del Carmen, M. (2015). La validación por juicio de expertos: Dos investigaciones cualitativas en Lingüística aplicada. Revista Nebrija de Lingüística Aplicada a La Enseñanza de Lenguas, 18, 1–16.
• Russell, J. S., Menassa, C. C., & McCloskey, E. (2014). Lifelong Learning to Leverage Project and Career Success: 21st-Century Imperative. Practice Periodical on Structural De sign and Con s t ru c tion, 19 (1 ) , 137–141 . https: //doi .org /10 .1061 / (ASCE)SC.1943-5576.0000201
• Sánchez, M. C. (2015). La dicotomía cualitativo-cuantitativo: Posibilidades de integración y diseños mixtos. Campo Abierto, Monográfico, 11–30.
• Sanchez-Gordon, S., & Luján-Mora, S. (2017). Research challenges in accessible MOOCs: A systematic literature review 2008–2016. Universal Access in the Information Society. https://doi.org/10.1007/s10209-017-0531-2
• Sangrà, A., González-Sanmamed, M., & Anderson, T. (2015). Meta-analysis of the research about MOOC during 2013-2014. Educación XX1, 18(2), 1-28. https://doi.org/ 10.5944/educxx1.14808
• Schuetze, H. G. (2006). International concepts and agendas of Lifelong Learning. Compare: A Journal of Comparative and International Education, 36(3), 289–306. https:// doi.org/10.1080/03057920600872381
• Shapiro, H. B., Lee, C. H., Wyman-Roth, N. E., Li, K., Çetinkaya-Rundel, M., & Canelas, D. A. (2017). Understanding the massive open online course (MOOC) student experience: An examination of attitudes, motivations, and barriers. Computers & Education, 110, 35–50. https://doi.org/10.1016/j.compedu.2017.03.003
• Siddiq, F., Gochyyev, P., & Wilson, M. (2017). Learning in Digital Networks – ICT literacy: A novel assessment of students’ 21st century skills. Computers & Education, 109, 11– 37. https://doi.org/10.1016/j.compedu.2017.01.014
• Silverman, D. (Ed.). (2016). Qualitative research (Fourth Edition). Sage.
• Stake, R. E. (2013). Multiple case study analysis. Guilford Press.
• Stuchlikova, L. (2016). Challenges of education in the 21st century. In S. Smokovec (Ed.), ICETA 2016—14th IEEE International Conference on Emerging eLearning Technologies and Applications, Proceedings (pp. 335–340). IEEE. https://doi.org/ 10.1109/ICETA.2016.7802072
• Suresh, S., & Mallikarjuna, P. M. (2019). Analysis of Student Engagement and Course Completion in Massive Open Online Courses. In A. N. Krishna, K. C. Srikantaiah, & C. Naveena (Eds.), Integrated Intelligent Computing, Communication and Security (Vol. 7 7 1 , p p . 4 4 7 – 4 5 8 ) . S p r i n g e r S i n g a p o r e . https : //doi.org / 10.1007/978-981-10-8797-4_46
• Taylor, S. J., Bogdan, R., & DeVault, M. L. (2016). Introduction to qualitative research methods: A guidebook and resource (Fourth edition). John Wiley & Sons, Inc.
• Tondeur, J., van Braak, J., & Valcke, M. (2007). Curricula and the use of ICT in education: Two worlds apart? British Journal of Educational Technology, 38(6), 962–976. https://doi.org/10.1111/j.1467-8535.2006.00680.x
• Tovar, E., & Piedra, N. (2014). Guest Editorial: Open Educational Resources in Engineering Education: Various Perspectives Opening the Education of Engineers. IEEE Transactions on Education, 57(4) , 213–219 . https://doi.org/10.1109/TE.2014.2359257
• Varol, F. (2013). Elementary school teachers and teaching with technology. TOJET: The Turkish Online Journal of Educational Technology, 12(3), 85–90.
• Whitehill, J., Mohan, K., Seaton, D., Rosen, Y., & Tingley, D. (2017). MOOC Dropout Prediction: How to Measure Accuracy? 161–164. https : //doi.org /10.1145/3051457.3053974
• Wiley, D. (2010). Openness as catalyst for an educational reformation. Educause Review, 4, 14–20.
• Wilson, M., Scalise, K., & Gochyyev, P. (2015). Rethinking ICT literacy: From computer skills to social network settings. Thinking Skills and Creativity, 18, 65–80. https://doi.org/ 10.1016/j.tsc.2015.05.001
• Wong, J., Baars, M., Davis, D., Van Der Zee, T., Houben, G.-J., & Paas, F. (2019). Supporting Self-Regulated Learning in Online Learning Environments and MOOCs: A Systematic Review. International Journal of Human–Computer Interaction, 35(4–5), 356–373. https://doi.org/10.1080/10447318.2018.1543084
• Xi, J., Chen, Y., & Wang, G. (2018). Design of a Personalized Massive Open Online Course Platform. International Journal of Emerging Technologies in Learning (IJET), 13(04), 58. https://doi.org/10.3991/ijet.v13i04.8470
• Zhang, H., Huang, T., Lv, Z., Liu, S., & Zhou, Z. (2017). MCRS: A course recommendation system for MOOCs. Multimedia Tools and Applications. https://doi.org/10.1007/ s11042-017-4620-2