Aprendizado de Domínio Aplicada à Educação Matemática, da Computação e Engenharias: um Mapeamento Sistemático
Resumo
O aprendizado de domínio é uma estratégia de aprendizagem individual, onde o aluno avança nos conteúdos ao seu próprio ritmo. Contudo, não existe uma visão geral acerca de como essa solução pode ser implementada, quais benefícios acadêmicos e desafios em aberto. Visando preencher essa lacuna, revisamos a literatura sobre o aprendizado de domínio em cursos da computação, matemática e engenharias, onde 40 artigos foram selecionados para esta revisão. Os resultados do estudo mostram diferentes abordagens de implementação, variando ganhos de desempenho acadêmico relatados, e desafios como custo de implementação e procrastinação dos alunos.
Palavras-chave:
aprendizado por domínio, mapeamento sistemático, STEM
Referências
Hillman, E. F., Figueroa, G. L., Morales, I. V., Papadopoulos, C., & Santiago-Román, A. I. (2021, July). Toward Benchmarking Student Progress in Mechanics: Assessing Learning Cycles through Mastery Learning and Concept Questions. In 2021 ASEE Virtual Annual Conference Content Access.
Ott, C., McCane, B., & Meek, N. (2021, June). Mastery Learning in CS1-An Invitation to Procrastinate?: Reflecting on Six Years of Mastery Learning. In Proceedings of the 26th ACM Conference on Innovation and Technology in Computer Science Education V. 1 (pp. 18-24).
Herman, G. L., Cai, Z., Bretl, T., Zilles, C., & West, M. (2020, August). Comparison of grade replacement and weighted averages for second-chance exams. In Proceedings of the 2020 ACM Conference on International Computing Education Research (pp. 56-66).
G. Sayeg-Sánchez and M. X. Rodríguez-Paz, 1Performance of college students in a statistics course using mastery learning," 2020 IEEE Global Engineering Education Conference (EDUCON), 2020, pp. 746-751, doi: 10.1109/EDUCON45650.2020.9125122.
G. Sayeg-Sánchez and M. X. Rodríguez-Paz, "Factors That Impact Mastery Learning in a Probability and Statistics Course," 2019 IEEE 11th International Conference on Engineering Education (ICEED), 2019, pp. 174-177, doi: 10.1109/ICEED47294.2019.8994920.
E. Baniassad, A. Campbell, T. Allidina and A. Ord, "Teaching Software Construction at Scale with Mastery Learning: A Case Study," 2019 IEEE/ACM 41st International Conference on Software Engineering: Software Engineering Education and Training (ICSE-SEET), 2019, pp. 182-191, doi: 10.1109/ICSE-SEET.2019.00027.
R. G. de Pontes, D. D. S. Guerrero, and J. C. A. de Figueiredo, “Analyzing Gamification Impact on a Mastery Learning Introductory Programming Course,” in Proceedings of the 50th ACM Technical Symposium on Computer Science Education, 2019, pp. 400–406, doi: 10.1145/3287324.3287367.
Stegeman, M. (2019, November). A set of exercises and tests for teaching tracing skills using a mastery approach. In Proceedings of the 19th Koli Calling International Conference on Computing Education Research (pp. 1-2).
Campbell, J., Petersen, A., & Smith, J. (2019, February). Self-paced mastery learning cs1. In Proceedings of the 50th acm technical symposium on computer science education (pp. 955-961).
Cutts, Q., Barr, M., Bikanga Ada, M., Donaldson, P., Draper, S., Parkinson, J., ... & Sundin, L. (2019, July). Experience Report: Thinkathon--Countering an
Ubaidullah, N., Hamid, J., & Mohamed, Z. (2019). Integrating the arcs motivational elements into an on-line game-based learning application: Does the application enhance students’ motivation in learning programming. International Journal of Innovative Technology and Exploring Engineering, 8(11), 1493-1501.
Segal, A., Gal, K., Shani, G., & Shapira, B. (2019). A difficulty ranking approach to personalization in E-learning. International Journal of Human-Computer Studies, 130, 261-272.
Y. M. Treviño and M. R. L. Cavazos, "Effects of immediate feedback using ICT in a CS1 course that implements Mastery Learning," 2018 IEEE Frontiers in Education Conference (FIE), 2018, pp. 1-5, doi: 10.1109/FIE.2018.8658845.
Hauswirth, M., & Adamoli, A. (2017, November). Metacognitive calibration when learning to program. In Proceedings of the 17th Koli Calling International Conference on Computing Education Research (pp. 50-59).
McCane, B., Ott, C., Meek, N., & Robins, A. (2017, January). Mastery learning in introductory programming. In Proceedings of the nineteenth australasian computing education conference (pp. 1-10).
Paiva, R. C., Ferreira, M. S., & Frade, M. M. (2017). Intelligent tutorial system based on personalized system of instruction to teach or remind mathematical concepts. Journal of Computer Assisted Learning, 33(4), 370-381.
Lim, E. W. C. (2017). A design software to facilitate learning via repeated practice by Chemical Engineering students. Education for Chemical Engineers, 21, 72-79.
Mullen, J., Byun, C., Gadepally, V., Samsi, S., Reuther, A., & Kepner, J. (2017). Learning by doing, High Performance Computing education in the MOOC era. Journal of Parallel and Distributed Computing, 105, 105-115.
Tíjaro-Rojas, R., Arce-Trigatti, A., Cupp, J., Pascal, J., & Arce, P. E. (2016). A Systematic and Integrative Sequence Approach (SISA) for mastery learning: Anchoring Bloom's Revised Taxonomy to student learning. Education for Chemical Engineers, 17, 31-43.
Ritter, S., Yudelson, M., Fancsali, S. E., & Berman, S. R. (2016, April). How mastery learning works at scale. In Proceedings of the Third (2016) ACM Conference on Learning@ Scale (pp. 71-79).
Mostafavi, B., Eagle, M., & Barnes, T. (2015, March). Towards data-driven mastery learning. In Proceedings of the Fifth International Conference on Learning Analytics And Knowledge (pp. 270-274).
A. Takahashi et al., "Design of advanced active and autonomous learning system for computing education — A3 learning system," 2015 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE), 2015, pp. 77-82, doi: 10.1109/TALE.2015.7386020.
F. C. S. Tiing, M. N. A. Azlan and H. K. Sam, "The development of DifITS," 2015 International Conference on Computer, Communications, and Control Technology (I4CT), 2015, pp. 304-308, doi: 10.1109/I4CT.2015.7219586.
D. Capovilla, M. Berges, A. Mühling and P. Hubwieser, "Handling Heterogeneity in Programming Courses for Freshmen," 2015 International Conference on Learning and Teaching in Computing and Engineering, 2015, pp. 197-203, doi: 10.1109/LaTiCE.2015.18.
M. Jazayeri, "Combining Mastery Learning with Project-Based Learning in a First Programming Course: An Experience Report," 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering, 2015, pp. 315-318, doi: 10.1109/ICSE.2015.163.
Kularbphettong, K., Kedsiribut, P., & Roonrakwit, P. (2015). Developing an adaptive web-based intelligent tutoring system using mastery learning technique. Procedia-Social and Behavioral Sciences, 191, 686-691.
O. M. Ashour, S. Sangelkar, R. L. Warley and O. Onipede, "Redesign the engineering teaching and assessment methods to provide more information to improve students' learning," 2014 IEEE Frontiers in Education Conference (FIE) Proceedings, 2014, pp. 1-6, doi: 10.1109/FIE.2014.7044286.
F. M. Capaldi, "Mastery learning in Statics using the STEMSI online learning environment," Proceedings of the 2014 Zone 1 Conference of the American Society for Engineering Education, 2014, pp. 1-3, doi: 10.1109/ASEEZone1.2014.6820671.
B. D. Mikula and A. F. Heckler, "The effectiveness of brief, spaced practice on student difficulties with basic and essential engineering skills," 2013 IEEE Frontiers in Education Conference (FIE), 2013, pp. 1059-1065, doi: 10.1109/FIE.2013.6684989.
Sophie Engle and Sami Rollins. 2013. Expert code review and mastery learning in a software development course. J. Comput. Sci. Coll. 28, 4 (April 2013), 139–147.
Shaffer, S. C., & Rosson, M. B. (2013). Increasing student success by modifying course delivery based on student submission data. ACM inroads, 4(4), 81-86.
Sabo, K. E., Atkinson, R. K., Barrus, A. L., Joseph, S. S., & Perez, R. S. (2013). Searching for the two sigma advantage: Evaluating algebra intelligent tutors. Computers in Human Behavior, 29(4), 1833-1840.
J. M. Bekki, O. Dalrymple and C. S. Butler, "A mastery-based learning approach for undergraduate engineering programs," 2012 Frontiers in Education Conference Proceedings, 2012, pp. 1-6, doi: 10.1109/FIE.2012.6462253.
Rae, A., & Samuels, P. (2011). Web-based Personalised System of Instruction: An effective approach for diverse cohorts with virtual learning environments?. Computers & education, 57(4), 2423-2431.
Shafie, N., Shahdan, T. N. T., & Liew, M. S. (2010). Mastery learning assessment model (MLAM) in teaching and learning mathematics. Procedia-Social and Behavioral Sciences, 8, 294-298.
Davrajoo, E., Tarmizi, R. A., Nawawi, M., & Hassan, A. (2010). Enhancing algebraic conceptual knowledge with aid of module using mastery learning approach. Procedia-Social and Behavioral Sciences, 8, 362-369.
LeJeune, N. (2010). Contract grading with mastery learning in CS 1. Journal of Computing Sciences in Colleges, 26(2), 149-156.
W. J. Leonard, C. V. Hollot and W. J. Gerace, "Mastering circuit analysis: An innovative approach to a foundational sequence," 2008 38th Annual Frontiers in Education Conference, 2008, pp. F2H-3-F2H-8, doi: 10.1109/FIE.2008.4720568.
D. Tian, "A progress-based online assessment system for first-year networking classes," Proceedings Frontiers in Education 35th Annual Conference, 2005, pp. S2H-31, doi: 10.1109/FIE.2005.1612251.
Urban-Lurain, M., & Weinshank, D. J. (1999). “I do and I understand” mastery model learning for a large non-major course. ACM SIGCSE Bulletin, 31(1), 150-154.
Ott, C., McCane, B., & Meek, N. (2021, June). Mastery Learning in CS1-An Invitation to Procrastinate?: Reflecting on Six Years of Mastery Learning. In Proceedings of the 26th ACM Conference on Innovation and Technology in Computer Science Education V. 1 (pp. 18-24).
Herman, G. L., Cai, Z., Bretl, T., Zilles, C., & West, M. (2020, August). Comparison of grade replacement and weighted averages for second-chance exams. In Proceedings of the 2020 ACM Conference on International Computing Education Research (pp. 56-66).
G. Sayeg-Sánchez and M. X. Rodríguez-Paz, 1Performance of college students in a statistics course using mastery learning," 2020 IEEE Global Engineering Education Conference (EDUCON), 2020, pp. 746-751, doi: 10.1109/EDUCON45650.2020.9125122.
G. Sayeg-Sánchez and M. X. Rodríguez-Paz, "Factors That Impact Mastery Learning in a Probability and Statistics Course," 2019 IEEE 11th International Conference on Engineering Education (ICEED), 2019, pp. 174-177, doi: 10.1109/ICEED47294.2019.8994920.
E. Baniassad, A. Campbell, T. Allidina and A. Ord, "Teaching Software Construction at Scale with Mastery Learning: A Case Study," 2019 IEEE/ACM 41st International Conference on Software Engineering: Software Engineering Education and Training (ICSE-SEET), 2019, pp. 182-191, doi: 10.1109/ICSE-SEET.2019.00027.
R. G. de Pontes, D. D. S. Guerrero, and J. C. A. de Figueiredo, “Analyzing Gamification Impact on a Mastery Learning Introductory Programming Course,” in Proceedings of the 50th ACM Technical Symposium on Computer Science Education, 2019, pp. 400–406, doi: 10.1145/3287324.3287367.
Stegeman, M. (2019, November). A set of exercises and tests for teaching tracing skills using a mastery approach. In Proceedings of the 19th Koli Calling International Conference on Computing Education Research (pp. 1-2).
Campbell, J., Petersen, A., & Smith, J. (2019, February). Self-paced mastery learning cs1. In Proceedings of the 50th acm technical symposium on computer science education (pp. 955-961).
Cutts, Q., Barr, M., Bikanga Ada, M., Donaldson, P., Draper, S., Parkinson, J., ... & Sundin, L. (2019, July). Experience Report: Thinkathon--Countering an
Ubaidullah, N., Hamid, J., & Mohamed, Z. (2019). Integrating the arcs motivational elements into an on-line game-based learning application: Does the application enhance students’ motivation in learning programming. International Journal of Innovative Technology and Exploring Engineering, 8(11), 1493-1501.
Segal, A., Gal, K., Shani, G., & Shapira, B. (2019). A difficulty ranking approach to personalization in E-learning. International Journal of Human-Computer Studies, 130, 261-272.
Y. M. Treviño and M. R. L. Cavazos, "Effects of immediate feedback using ICT in a CS1 course that implements Mastery Learning," 2018 IEEE Frontiers in Education Conference (FIE), 2018, pp. 1-5, doi: 10.1109/FIE.2018.8658845.
Hauswirth, M., & Adamoli, A. (2017, November). Metacognitive calibration when learning to program. In Proceedings of the 17th Koli Calling International Conference on Computing Education Research (pp. 50-59).
McCane, B., Ott, C., Meek, N., & Robins, A. (2017, January). Mastery learning in introductory programming. In Proceedings of the nineteenth australasian computing education conference (pp. 1-10).
Paiva, R. C., Ferreira, M. S., & Frade, M. M. (2017). Intelligent tutorial system based on personalized system of instruction to teach or remind mathematical concepts. Journal of Computer Assisted Learning, 33(4), 370-381.
Lim, E. W. C. (2017). A design software to facilitate learning via repeated practice by Chemical Engineering students. Education for Chemical Engineers, 21, 72-79.
Mullen, J., Byun, C., Gadepally, V., Samsi, S., Reuther, A., & Kepner, J. (2017). Learning by doing, High Performance Computing education in the MOOC era. Journal of Parallel and Distributed Computing, 105, 105-115.
Tíjaro-Rojas, R., Arce-Trigatti, A., Cupp, J., Pascal, J., & Arce, P. E. (2016). A Systematic and Integrative Sequence Approach (SISA) for mastery learning: Anchoring Bloom's Revised Taxonomy to student learning. Education for Chemical Engineers, 17, 31-43.
Ritter, S., Yudelson, M., Fancsali, S. E., & Berman, S. R. (2016, April). How mastery learning works at scale. In Proceedings of the Third (2016) ACM Conference on Learning@ Scale (pp. 71-79).
Mostafavi, B., Eagle, M., & Barnes, T. (2015, March). Towards data-driven mastery learning. In Proceedings of the Fifth International Conference on Learning Analytics And Knowledge (pp. 270-274).
A. Takahashi et al., "Design of advanced active and autonomous learning system for computing education — A3 learning system," 2015 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE), 2015, pp. 77-82, doi: 10.1109/TALE.2015.7386020.
F. C. S. Tiing, M. N. A. Azlan and H. K. Sam, "The development of DifITS," 2015 International Conference on Computer, Communications, and Control Technology (I4CT), 2015, pp. 304-308, doi: 10.1109/I4CT.2015.7219586.
D. Capovilla, M. Berges, A. Mühling and P. Hubwieser, "Handling Heterogeneity in Programming Courses for Freshmen," 2015 International Conference on Learning and Teaching in Computing and Engineering, 2015, pp. 197-203, doi: 10.1109/LaTiCE.2015.18.
M. Jazayeri, "Combining Mastery Learning with Project-Based Learning in a First Programming Course: An Experience Report," 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering, 2015, pp. 315-318, doi: 10.1109/ICSE.2015.163.
Kularbphettong, K., Kedsiribut, P., & Roonrakwit, P. (2015). Developing an adaptive web-based intelligent tutoring system using mastery learning technique. Procedia-Social and Behavioral Sciences, 191, 686-691.
O. M. Ashour, S. Sangelkar, R. L. Warley and O. Onipede, "Redesign the engineering teaching and assessment methods to provide more information to improve students' learning," 2014 IEEE Frontiers in Education Conference (FIE) Proceedings, 2014, pp. 1-6, doi: 10.1109/FIE.2014.7044286.
F. M. Capaldi, "Mastery learning in Statics using the STEMSI online learning environment," Proceedings of the 2014 Zone 1 Conference of the American Society for Engineering Education, 2014, pp. 1-3, doi: 10.1109/ASEEZone1.2014.6820671.
B. D. Mikula and A. F. Heckler, "The effectiveness of brief, spaced practice on student difficulties with basic and essential engineering skills," 2013 IEEE Frontiers in Education Conference (FIE), 2013, pp. 1059-1065, doi: 10.1109/FIE.2013.6684989.
Sophie Engle and Sami Rollins. 2013. Expert code review and mastery learning in a software development course. J. Comput. Sci. Coll. 28, 4 (April 2013), 139–147.
Shaffer, S. C., & Rosson, M. B. (2013). Increasing student success by modifying course delivery based on student submission data. ACM inroads, 4(4), 81-86.
Sabo, K. E., Atkinson, R. K., Barrus, A. L., Joseph, S. S., & Perez, R. S. (2013). Searching for the two sigma advantage: Evaluating algebra intelligent tutors. Computers in Human Behavior, 29(4), 1833-1840.
J. M. Bekki, O. Dalrymple and C. S. Butler, "A mastery-based learning approach for undergraduate engineering programs," 2012 Frontiers in Education Conference Proceedings, 2012, pp. 1-6, doi: 10.1109/FIE.2012.6462253.
Rae, A., & Samuels, P. (2011). Web-based Personalised System of Instruction: An effective approach for diverse cohorts with virtual learning environments?. Computers & education, 57(4), 2423-2431.
Shafie, N., Shahdan, T. N. T., & Liew, M. S. (2010). Mastery learning assessment model (MLAM) in teaching and learning mathematics. Procedia-Social and Behavioral Sciences, 8, 294-298.
Davrajoo, E., Tarmizi, R. A., Nawawi, M., & Hassan, A. (2010). Enhancing algebraic conceptual knowledge with aid of module using mastery learning approach. Procedia-Social and Behavioral Sciences, 8, 362-369.
LeJeune, N. (2010). Contract grading with mastery learning in CS 1. Journal of Computing Sciences in Colleges, 26(2), 149-156.
W. J. Leonard, C. V. Hollot and W. J. Gerace, "Mastering circuit analysis: An innovative approach to a foundational sequence," 2008 38th Annual Frontiers in Education Conference, 2008, pp. F2H-3-F2H-8, doi: 10.1109/FIE.2008.4720568.
D. Tian, "A progress-based online assessment system for first-year networking classes," Proceedings Frontiers in Education 35th Annual Conference, 2005, pp. S2H-31, doi: 10.1109/FIE.2005.1612251.
Urban-Lurain, M., & Weinshank, D. J. (1999). “I do and I understand” mastery model learning for a large non-major course. ACM SIGCSE Bulletin, 31(1), 150-154.
Publicado
16/11/2022
Como Citar
ARANHA, Eduardo Henrique da S.; CARNEIRO, Jairo Rodrigo S.; SANTANA, Alan de O..
Aprendizado de Domínio Aplicada à Educação Matemática, da Computação e Engenharias: um Mapeamento Sistemático. In: SIMPÓSIO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (SBIE), 33. , 2022, Manaus.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2022
.
p. 1087-1101.
DOI: https://doi.org/10.5753/sbie.2022.225224.
