Reconhecemos nos estudos realizados que o conjunto pequeno e uniforme de estudantes que gerou as ações registradas nos logs e a semelhança de conteúdos dos vídeos pode ter influenciado a capacidade de generalização dos resultados apresentados. Por essa razão, recomendamos como trabalho futuro uma ampliação do conjunto de dados com um número maior de estudantes, de disciplinas e de cursos.
Durante o estudo da seção 6, mencionamos o desenvolvimento de uma aplicação para limpeza e extração de dados dos arquivos de log. Essa aplicação necessita de melhorias que a tornem utilizável de maneira intuitiva e completa por parte dos professores. Portanto, sugerimos o complemento e a validação dela como trabalho futuro.
Uma outra recomendação diz respeito à utilização da mineração de processos: é preciso efetuar testes de desempenho e de checagem dos modelos gerados através de medidas como fitness e precisão, além de efetuar testes com outros algoritmos com fins de comparação entre eles.
REFERÊNCIAS BIBLIOGRÁFICAS
AALST, W.M.P van der. Process Mining: A historical Perspective Keynote Process Mining Camp, Fluxicon, Eindhoven. 2013
AALST, W.M.P van der. Process Mining: Beyond Business Intelligence. Technische Universiteit Eindhoven Technical Tutorial. Disponível em
<http://www.processmining.org/_media/presentations/processminingtutorialesscass- 2009.pdf> acesso em 10 de junho de 2017
AALST, W.M.P van der. Process Mining: Discovering and Improving Spaghetti and Lasagna Processes. In: IEEE Symposium on Computational Intelligence and Data Mining (CIDM). 2011
AALST, W.M.P van der. Process Mining: Overview and Opportunities. ACM Transactions on Management Information Systems (TMIS). Volume 3 Issue 2. Article No. 7. Julho de 2012.
AALST, W.M.P van der.; Guo, Shengnan e Gorissen, Pierre. Comparative Process Mining in Education: An Approach Based on Process Cubes. In: IFIP International Federation for Information Processing, SIMPDA 2013, LNBIP 203, pp. 110–134. 2015. DOI: 10.1007/978- 3-662-46436-6 6
AALST, W.M.P van der.; WEIJTERS, A.; MARUSTER, L. 2004. Workflow mining: Discovering process models from event logs. IEEE Trans. Knowl. Data Engin. 16, 9, 1128– 1142.
AALST, W.M.P. van der. Process Mining - Discovery, Conformance and Enhancement of Business Process, SPRINGER. 2011
ADNAN, H., REDZUAN, F. Evaluating students' emotional response in video-based learning using Kansei Engineering,. In Proceedings 4th International Conference on User Science and Engineering, i-USEr. 2017
ARORA, Skand; GOEL, Manav; SABITHA, A. S. & MEHROTRA, Deepti. Learner Groups in Massive Open Online Courses. The American Journal of Distance Education. 2017. BACK, M. Using Facebook Data to Analyze Leamer Interaction During Study Abroad, Foreign Language Annals, vol. 46(3), pp. 377-401. doi:10.1III/tan.12036. 2013
BAIDYA, E., GOEL, S. LectureKhoj: Automatic Tagging and Semantic Segmentation of Online Lecture Videos. 7th International Conference on Contemporary Computing, IC3. 2014 BALASUBRAMANIAN, V., DORAISAMY, S. G., KANAKARAJAN, N. K. A multimodal approach for extracting content descriptive metadata from lecture vídeos. Journal of
Intelligent Information Systems. 2015
BASU, S., Yu, Y., ZIMMERMANN, R. Fuzzy Clustering of Lecture Videos Based on Topic Modeling. International Workshop on Content-Based Multimedia Indexing. 2016
BEATTY, B. J., MERCHANT, Z., ALBERT, M. Beatty. Analysis of Student Use of Video in a Flipped Classroom. TechTrends. 2017
BRESLOW, L., et al.., Studying learning in the worldwide classroom: Research into edX's first MOOC, in RESEARCH & PRACTICE IN ASSESSMENT. p. 13-25, 2013.
BROOKS, C., EPP, C. D., LOGAN, G., GREER, J. The who, what, when, and why of lecture capture. Learning Analytics & Knowledge (LAK). 2011
BROTHERTON, J.; ABOWD, G. Lessons learned from eclass: Assessing automated capture and access in the classroom”. In: ACM Transactions on Computer-Human Interaction, vol 11, 2, ACM Press, pp. 121–155. 2004
BRUCKMAN, A. Analysis of log fle data to understand behavior and learning in an online community. The International Handbook of Virtual Learning Environments, pp. 1449-1465, doi:10.1007/978-1-4020-3803-7_58. 2006
CABENA, P.; HADJINIAM, P.; STADLER, R.; VERHEES, J.; ZANASI, A. Discovering data mining: from concept to implementation. Upper Sadle River: Prentice Hall, Engle-wood Cliffs, NJ. 1998.
CHA, S.; KIM, W. The Analysis of Learner’s Concentration by Facial Expression Changes & Movements”. In International Journal of Applied Engineering Research ISSN 0973-4562 V.11, N.23, pp. 11344-11349. 2016
CHAUHAN, J., GOEL, A. An Analysis of Video Lecture in MOOC. CEUR Workshop Proceedings. 2015
CHE, X., LUO, S., YANG, H., MEINEL, C. Sentence-level automatic lecture highlighting based on acoustic analysis. IEEE International Conference on Computer and Information Technology. 2016a
CHE, X., STAUBITZ, T., YANG, H., MEINEL, C. Pre-course key segment analysis of online lecture videos. IEEE 16th International Conference on Advanced Learning Technologies. 2016b
CHORIANOPOULOS, K. Collective intelligence within web video. Human-centric Computing and Information Sciences 3, 1. 10. 2013
CHORIANOPOULOS, K. e GIANNAKOS, M. N. “Usability design for video lectures,” The 11th European Conference on Interactive TV and Video, Como. Italy, pp. 163-164. 2013 COCEA, M. and WEIBELZAHL, S. Log file analysis for disengagement detection in e- Learning environments. User Modeling and User-Adapted Interaction, vol. 19, pp.341- 385,doi:1O.1007/s11257-009-9065-5. 2009
DE MAIO, C., LOIA, V., MANGIONE, G. R., ORCIUOLI, F. Automatic generation of SKOS taxonomies for generating topic-based user interfaces in MOOCs. Lecture Notes in Computer Science / EC-TEL 2014, LNCS 8719. 2014
DESMARAIS, M., VILLAREAL, A., e GAGNON, M., Adaptive test design with a naïve bayes framework. In First International Conference on EDM, Montreal, Canada, 2008. DISCO. Disco Users Guide. Disponível em: https://fluxicon.com/disco/files/Disco-User- Guide.pdf. Acesso em 25/10/2017
DYBÅ, T., DINGSØYR, T. Empirical studies of agile software development: a systematic review. Information and Software Technology, 50, pp. 833-859. 2008
EDWARDS, A., MASSICCI, A., SRIDHARAN, S., GEIGEL, J., WANG, L., BAILEY, R., ALM, C.O. Sensor-based methodological observations for studying online learning. ACM Workshop on Intelligent Interfaces for Ubiquitous and Smart Learning (SmartLearn’17). 2017 ESTACIO, Rosalina Rebucas e RAGA JR, Rodolfo Callanta. Analyzing students online learning behavior in blended courses using Moodle", Asian Association of Open Universities Journal, Vol. 12 Issue: 1, pp.52-68, 2017.
FAYYAD, Usama M.; PIATETSKY-SHAPIRO, Gregory; SMYTH, Padhraic. From data mining to knowledge discovery: an overview, Advances in knowledge discovery and data mining, American Association for Artificial Intelligence, Menlo Park, CA, 1996
FREITAS, F. F.T., PELAES, T.S., CARNEIRO, M.P. Process Mining: Aplicações Envolvendo Descoberta e Análise de Conformidade de Processos. In: XXIX Encontro Nacional de Engenharia de Produção, 2009, Salvador/BA. Anais. Salvador/BA, 2009. FURINI, M. On introducing timed tag-clouds in video lectures indexing. Multimedia Tools and Applications, Springer US, 2017
GIANNAKOS, M. N.; CHORIANOPOULOS, K.; CHRISOCHOIDES, N. Collecting and Making Sense of Video Learning Analytics”. In: IEEE Frontiers in Education Conference (FIE). 2015
GÜNTHER C.W., AALST, W.M.P. van der. Fuzzy Mining – Adaptive Process
Simplification Based on Multi-perspective Metrics. In: Alonso G., Dadam P., Rosemann M. (eds) Business Process Management. BPM 2007. Lecture Notes in Computer Science, vol 4714. Springer, Berlin, Heidelberg. 2007
GUO, Philip J., KIM, Juho & RUBIN, Rob. How video production affects student
engagement: an empirical study of MOOC videos. Proceedings of the first ACM conference on Learning @ scale conference. Pages 41-50. 2014
GUPTA, E. Process Mining Algorithms. International Journal of Advance Research in Science and Engineering 3(11), .401-412. 2014
HADDIOUI, I.; KHALDI, Mohamed. Learner Behavior Analysis through Eye Tracking. In International Journal of Computer Science Research and Application, V.2, I.2, pp. 11-18. 2012
HAN, J., KAMBER, M. e PEI, Jian. Data Mining: Concepts and Techniques, 3ª edição, The Morgan Kaufmann Series. 2012
HAND,David J., MANNILA, Heikki e SMYTH,Padhraic. Principles of data mining, MIT Press, Cambridge, MA, 2001.
HARRER, A., VETTER, M., THUR, S., e BRAUCKMANN, J. Discovery of Patterns in Learner Actions. Proc. International Conference on Artifcial Intelligence in Education, pp.816-818. 2005
HUANG, Nen-Fu; HSU, Hao-Hsuan; CHEN, So-Chen; LEE, Chia-An; HUANG, Yi-Wei; OU, Po-Wen. VideoMark: A Video-Based Learning Analytic Technique for MOOCs. Em IEEE 2nd International Conference on Big Data Analysis (ICBDA). 2017
JADIN, T.; GRUBER, A.; BATINIC, B. Learning with E-lectures: The Meaning of Learning Strategies,” Educational Technology & Society, vol 12, 3, pp. 282–288. 2009
KADOIĆ, N. e OREŠKI, D. "Analysis of student behavior and success based on logs in Moodle". 41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), Opatija, pp. 0654-0659, 2018.
KIM, J., GUO, P. J., CAI, C. J., LI, S.-W., GAJOS, K. Z., MILLER, R. C. Data-driven interaction techniques for improving navigation of educational videos. Symposium on User Interface Software and Technology - UIST’14. 2014
KITCHENHAM, B.A.; BUDGEN, D. e BRERETON, P. Evidence-based software engineering and systematic reviews. CRC Press. 2016.
KIZILCEC, R.F., BISSONNETTE, R. Deconstructing disengagement: analyzing learner subpopulations in massive open online courses. in LAK '13 Proceedings of the Third International Conference on Learning Analytics and Knowledge. New York. 2013
KLEFTODIMOS, A., EVANGELIDIS, G. An interactive video-based learning environment that supports learning analytics for teaching 'Image Editing'. SE@VBL 2016 workshop at LAK’16. 2016.
KUO, Y.-Y., LUO, J., BRIELMAIER, J. Investigating students’ use of lecture videos in online courses: A case study for understanding learning behaviors via data mining. Lecture Notes in Computer Science - ICWL 2015, LNCS. 2015.
LANG, C., SIEMENS, G., WISE, A., & GASEVIC, D. (Eds.) Handbook of learning analytics. SOLAR. 2017
LEEMANS, Sander J.J.. Inductive visual Miner – manual. Prom 6.7. 2017
LI, Nan; KIDZINSKI, Lukasz; JERMANN, Patrick e DILLENBOURG, Pierre. MOOC Video Interaction Patterns: What Do They Tell Us? Lecture Notes in Computer Science, v.9307. Springer. 2015
MARTIN, F. G. Will massive open online courses change how we teach? Communications of the ACM, 55, 8, 26–28. 2012
MEDEIROS, A., WEIJTERS, A., AND VAN DER AALST, W. Genetic process mining: An experimental evaluation. Data Mining Knowl. Discov. 14, 2, 245–304. 2007
MUKALA, P., BUIJS, J., LEEMANS, M., e AALST, W.M.P. van der. Learning analytics on coursera event data: a process mining approach. In P. Caravolo, & S. Rinderle-Ma (Eds.), Proceedings of the 5th International Symposium on Data-driven Process Discovery and Analysis (SIMPDA 2015), Vienna, Austria, December 9-11 (pp. 18-32). (CEUR Workshop Proceedings; Vol. 1527). CEUR-WS.org. 2015
MUÑOZ-MERINO, P J., RUIPÉREZ-VALIENTE, J. A., ALARIO-HOYOS, C., PÉREZ- SANAGUSTÍN, M., DELGADO KLOOS, C. Precise Effectiveness Strategy for analyzing the
effectiveness of students with educational resources and activities in MOOCs. Computers in Human Behavior. 2015.
MURATA, T. Petri Nets: Properties, Analysis and Applications. Proceedings of the IEEE, 77(4):541–580, abril de 1989.
NAN LI, Lukasz Kidzinski, JERMANN, Patrick, e DILLENBOURG, Pierre. MOOC Video Interaction Patterns: What Do They Tell Us? Lecture Notes in Computer Science, v.9307. Springer. 2015
REISIG, W. e ROZENBERG, G. (eds). Lectures on Petri Nets I: Basic Models, volume 1491 of Lecture Notes in Computer Science. Springer-Verlag, Berlin, 1998.
ROMERO, C.; VENTURA S.; PECHENIZKIY, M. e BAKER, R. Handbook of Educational Data Mining, Boca Raton, FL: CRC Press, Taylor&Francis, 2010.
ROZINAT, A.; VAN DER AALST, W.M.P. Conformance checking of processes based on monitoring real behavior. In: Information Systems. Volume 33, Issue 1, Pages 64-95, março de 2008.
ROZINAT, Anne, Process Mining:Conformance and Extension,Technische Universiteit Eindhoven - Proefschrift. 2010
SANTANA, A. L. M. Análise do processo metodológico de montagem de um brinquedo de programar. 2015. 93 f. Dissertação (Mestrado) - Curso de Computação Aplicada,
Universidade do Vale de Itajaí, Itajaí, 2015.
SCHILTZ, G. Video Analytics: when and how do students use tutorial videos?. In: 23rd International Conference on Computers in Education. China: Asia-Pacific Society for Computers in Education. 2015
SOFFER, Tal; KAHAN, Tali e LIVNE, Eynat. E-assessment of online academic courses via students' activities and perceptions. Studies in Educational Evaluation. Volume 54. Pages 83- 93, setembro de 2017
TOHIDI, Hamid; JABBARI, Mohammad Mehdi. The effects of motivation in education. In WCLTA 2011. Procedia - Social and Behavioral Sciences 31. 820 – 824, 2012
TRČKA, N.; PECHENIZKIY, M and Van der Aalst, W.P.M. Process mining from
educational data (Chapter 9)," In Handbook of Educational Data Mining, CRC Press, pp. 123- 142, 2010.
VERBEEK, H.M.W.; BUIJS, J.C.A.M.; van DONGEN, B.F.; AALST, W.M.P. van der. Prom 6: The Process Mining, Toolkit. In Proc. of BPM Demonstration Track 2010, M. L. Rosa, Ed. CEUR Workshop Proceedings Series, vol. 615. 3439. 2010
WANG, Wen-Fang; CHEN, Chih-Ming; WU, Chung-Hsin. Effects of Different Video Lecture Types on Sustained Attention, Emotion, Cognitive Load, and Learning Performance. 4th International Congress on Advanced Applied Informatics. Okayama, Japão. 2015
WEBER, M. A. L.; BEHRENS, M. A. Paradigmas educacionais e o ensino com a utilização de mídias. Revista Intersaberes. Curitiba, a. 5, n. 10, p. 245-270, jul./dez. 2010.
WEIJTERS A. J. M. M.; AALST, WMP van der e MEDEIROS, A.K.A. Process mining with the heuristics miner-algorithm. Technische Universiteit Eindhoven Technical Report WP; 166: 1-34. 2006
WILEY, D. Connecting learning objects to instructional design theory: A defnition, a metaphor, and a taxonomy. The Instructional Use of Learning Objects, Wiley, D.A. (ed.), Association for Educational Communications and Technology, Bloomington, IN, 2002
YIN, Chengjiu; UOSAKI, Noriko; CHU, Hui-Chun; HWANG, Gwo-Jen; HWANG, Jau-Jian; HATONO, Itsuo; KUMAMOTO, Etsuko; TABATA, Yoshiyuki. Learning Behavioral Pattern Analysis based on Students' Logs in Reading Digital Books. 2017