Linha de Pesquisa: Interfaces Digitais em Educação, Arte, Linguagem e Cognição
Turma: GA (Gabriela)
Código da Disciplina: PIE00021 – Seminário Avançado
Título da Disciplina: Learning analytics em MOOC
Professor Responsável: Gabriela Trindade Perry
Disciplina destinada a:
- Alunos Regulares do PPGIE: 14 vagas
- Orientandos: 03 vagas
- Outros PPGs da UFRGS: 05 vagas
- Alunos PEC: 02 vagas (o aluno deverá solicitar a vaga por e-mail para o professor responsável pela disciplina)
Dia da semana: sextas-feiras
Horário: 09:30 – 12:00
Créditos: 4
Carga-horária: 4 h/a
Data de início da disciplina (primeira aula): 21/08/2020
Data de término da disciplina (última aula): 27/11/2020
Local: Mconf
Recursos necessários na sala: computador, projetor, internet, Excel/Libre Office Calc, R Studio (livre e gratuito)
Súmula/ementa:
- Introdução aos MOOC e ao estudo do comportamento dos estudantes na plataforma Lúmina, com foco na análise do aproveitamento e dos fatores que levam ao abandono do curso. Investigação usando relatórios de navegação, apoiados em técnicas estatísticas e exploratórias.
Objetivos:
- Avaliar o alcance da técnica de Learning Analytics em MOOC
- Discutir formas de enriquecer a coleta de dados a respeito do comportamento dos estudantes de MOOC
- Redação de artigo sobre os temas abordados nas aulas.
Programa (conteúdo):
- Plataformas e cursos – recursos tecnológicos, suporte à tarefas e conteúdos.
- Tipos de cursos – cMooc, xMOOC, nanoMOOC
- Características de MOOC – elementos estruturais, público-alvo, interatividade, funcionamento, avaliação, certificação.
- Motivos para adesão e abandono
- Formas de avaliação
- Tipos de dados que podem ser coletados em plataformas de MOOC. Que perguntas podem ser respondidas? O que fica encoberto? Limitações das análises.
- Bases de dados abertas.
- Ferramentas de análise de dados – estatística descritiva, inferencial, exploratória
Método de trabalho (principais atividades):
- Aulas gravadas em formato de áudio e vídeo, reuniões (virtuais), correção de trabalho colaborativa, redação de artigos
Procedimentos e/ou critérios de avaliação:
- Participação e engajamento nas atividades
- Correção de trabalhos dos colegas (peer review)
- Redação de artigo
Bibliografia recomendada:
A bibliografia será postada no MOODLE. A lista dos artigos, de acordo com o tema segue abaixo. Obviamente, os alunos são incentivados a buscar outras referências.
Ajitiono, Try; Widyani, Yani. 2016. Indonesian essay grading module using Natural Language Processing. International Conference on Data and Software Engineering (ICoDSE), Denpasar, 2016, pp. 1-5
Analytics and Knowledge (LAK 2013),3., 8-12 April 2013. Proceedings…Leuven, Belgium, p. 185-189.
Badea, G., Popescu, E., Sterbini, A., & Temperini, M. (2019). Integrating Enhanced Peer Assessment Features in Moodle Learning Management System. In Lecture Notes in Educational Technology (pp. 135–144).
Balfour, S. P. (2013). Assessing Writing in MOOCs: Automated Essay Scoring and Calibrated Peer Review. Research & Practice in Assessment, , 13–26
Baturay, 2015. An overview of the world of MOOCs. Procedia – Social and Behavioral Sciences
Claypool, M., Le, P., Waseda, M., and Brown, D. (2001). Implicit interest indicators. In Proceedings of the 6th International Conference on Intelligent User Interfaces (IUI ’01), USA, 33-40.
Clow, D. 2017. MOOC and the funnel of participation. In: Conference on Learning
Clustering patterns of engagement in Massive Open Online Courses (MOOCs): the use of learning analytics to reveal student categories.
Cohen, A., & Baruth, O. (2017). Personality, learning, and satisfaction in fully online academic courses. Computers in Human Behavior, 72, 1–12
Conole, G. 2013. MOOCs as disruptive technologies: Strategies for enhancing the learner experience and quality of MOOCs. e-Lis.
DeBoer, J. et all. 2014. Changing “Course”: Reconceptualizing Educational Variables for Massive Open Online Courses. Educational Researcher, 43(2), 74-84.
Deng, R., & Benckendorff, P. (2017). A Contemporary Review of Research Methods Adopted to Understand Students’ and Instructors’ Use of Massive Open Online Courses (MOOCs).
Deng, R., Benckendorff, P., & Gannaway, D. (2019). Progress and new directions for teaching and learning in MOOCs. Computers and Education, 129, 48–60.
Eriksson, T.; Adawi, t.; Stöhr, c. “Time is the bottleneck”: a qualitative study exploring why learners drop out of MOOCs. Journal of Computing in Higher Education, vol. 29, n. 1, p. 133-146, 2017.
Garcia-Loro, F., Martin, S., Ruipérez-Valiente, J. A., Sancristobal, E., & Castro, M. (2020). Reviewing and analyzing peer review Inter-Rater Reliability in a MOOC platform. Computers and Education, 154.
Hew, K. F., & Cheung, W. S. (2014). Students’ and instructors’ use of massive open online courses (MOOCs): Motivations and challenges. Educational Research Review
Hone, K. S., & El Said, G. R. (2016). Exploring the factors affecting MOOC retention: A survey study. Computers and Education, 98, 157–168.
Horizons). Educause Review, 2013. p. 62–63.
Jacobsen, D. Y. 2019. Dropping Out or Dropping In? A Connectivist Approach to Understanding Participants’ Strategies in an e-Learning MOOC Pilot. Technology, Knowledge and Learning, vol. 24, n.1, p. 1-21
Kelly, K.; Teevan, J. 2013. Implicit feedback for inferring user preference: a bibliography. SIGIR Forum, August 2003 , Vol 37(2).
Kizilcec, R. F., Pérez-Sanagustín, M., & Maldonado, J. J. (2017). Self-regulated learning strategies predict learner behavior and goal attainment in Massive Open Online Courses. Computers and Education, 104, 18–33.
Koller, D. et al. 2013. Retention and Intention in Massive Open Online Courses (New
Littlejohn, A., Hood, N., Milligan, C., & Mustain, P. (2016). Learning in MOOCs: Motivations and self-regulated learning in MOOCs. Internet and Higher Education, 29, 40–48.
Liyanagunawardena, T. R. et al. 2019. A MOOC Taxonomy Based on Classification Schemes of MOOCs. European Journal of Open, Distance and e-Learning. 22(1)
Liyanagunawardena, T. R., Adams, A. A., & Williams, S. A. (2013). MOOCs: A systematic study of the published literature 2008-2012. International Review of Research in Open and Distance Learning, 14(3), 202–227.
Martin Formanek, Matthew C. Wenger, Sanlyn R. Buxner, Chris D. Impey, Tenzin Sonam. 2017. Insights about large-scale online peer assessment from an analysis of an astronomy MOOC. Computers & Education 113, p. 243-262
MOOC. ACM Conference on computer supported cooperative
Pappano, L. The Year of the MOOC. The New York Times, p. 1-7, 2012.
Paton, R. M., Fluck, A. E., & Scanlan, J. D. (2018). Engagement and retention in VET MOOCs and online courses: A systematic review of literature from 2013 to 2017. Computers and Education, 125, 191–201.
Pilli, A.; Admiraal, W. A Taxonomy of Massive Open Online Courses. Contemporary Educational Technology, vol. 7, n. 3, p. 223-240, 2016.
Prior, D. D., Mazanov, J., Meacheam, D., Heaslip, G., & Hanson, J. (2016). Attitude, digital literacy and self efficacy: Flow-on effects for online learning behavior. Internet and Higher Education, 29, 91–97.
Raffaghelli, J. E., Cucchiara, S., & Persico, D. (2015). Methodological approaches in MOOC research: Retracing the myth of Proteus. British Journal of Educational Technology, 46(3), 488–509.
Rafter, R., and Smyth, B. (2001). Passive profiling from server logs in an online recruitment environment. In Proceedings of the IJCAI Workshop on Intelligent Techniques for Web Personalization (ITWP 2001), USA, 35-41.
Reich & Ruipérez-Valiente, 2019. The MOOC pivot.
Rhoads et al, 2015. The Massive Open Online Course Movement, xMOCs, and Faculty Labor. The Review Of Higher Education, [s.l.], v. 38, n. 3, p.397-424, 2015
Rosselle, M., Caron, P. A., Heutte, J. 2014. A typology and dimensions of a description framework for MOOCs. European MOOCs Stakeholders Summit 2014, eMOOCs 2014, Feb 2014, Lausanne, France. pp.130-139
Shen, D., Cho, M. H., Tsai, C. L., & Marra, R. (2013). Unpacking online learning experiences: Online learning self-efficacy and learning satisfaction. Internet and Higher Education, 19, 10–17.
Using multi-platform learning analytics to compare regional and global MOOC learning in the Arab world.
Yuan & Powell, 2013. MOOCs and Open Education: Implications for Higher Education. Jisc Cetis. Whitepaper
Zheng, S. et al. 2015. Understanding Student Motivation, Behaviors and Perceptions in
Zhu, M., Sari, A., & Lee, M. M. (2018). A systematic review of research methods and topics of the empirical MOOC literature (2014–2016). Internet and Higher Education, 37, 31–39.