The Influence of Mathematics Learning Playlists in Student's Understanding
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Abstract
This study examines the influence of Mathematics Learning Playlists on student’s understanding of mathematical concepts, specifically in the topic of combinatorics. Utilizing the SAM (Successive Approximation Model) as the framework for development, the learning playlists were designed to provide structured, engaging, and self-paced learning experiences. The researcher-developed learning playlists consisted of researcher-made video lessons, self-learning activities (SLA), exercises, and quizzes. These were evaluated, then implemented among the purposively selected forty-one (41) Grade 10 Junior High School students in one of the public schools in Iligan City. The study employed a descriptive research design, measuring students’ performance through pre-test and post-test assessments to determine the influence of the intervention. A paired t-test was conducted to analyze the difference in scores, revealing statistically significant improvement in student’s understanding on Combinatorics after using the learning playlists. Students claimed that the Mathematics learning playlists helped them to understand the Combinatorics. The respondents perceived that the learning playlists was easy to follow, offering clear explanations, step-by-step solutions, flexible to revisit lessons anytime, and they overwhelmingly recommend Mathematics learning playlists as a valuable tool in teaching and learning. These findings indicate that Mathematics learning playlists serve as an instructional tool in enhancing conceptual understanding and academic performance. The study recommends the wider adoption of this strategy in mathematics education and further research on its long-term impact across different grade levels and mathematical domains.
Keywords— Mathematics Learning Playlists, student understanding, SAM model, combinatorics, self-paced learning
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References
Alami, Y. (2020). The impact of digital learning playlists on student engagement and academic performance in secondary education. Journal of Educational Technology, 35(2), 134–148.
Allen, M. W. (2012). Leaving ADDIE for SAM: An agile model for developing the best learning experiences. American Society for Training and Development.
Artzt, A. F., & Armour-Thomas, E. (1992). Development of a cognitive-metacognitive framework for protocol analysis of mathematical problem solving in small groups. Cognition and Instruction, 9(2), 137–175.
Ashcraft, M. H., & Moore, A. M. (2009). Mathematics anxiety and the affective drop in performance. Journal of Psychoeducational Assessment, 27(3), 197–205.
Baroody, A. J., Feil, Y., & Johnson, A. R. (2015). Teaching and learning mathematics in the digital age. Educational Technology & Society, 18(3), 101–115.
Bawa, P. (2016). Retention in online courses: Exploring issues and solutions—A literature review. SAGE Open, 6(1), 1–11.
Bergmann, J., & Sams, A. (2012). Flip your classroom: Reach every student in every class every day. International Society for Technology in Education.
Bergstrom, A., & Yamkovenko, B. (2024, January 22). University of Toronto randomized controlled trial demonstrates a meaningful positive effect of Khan Academy on student learning. Khan Academy. https://blog.khanacademy.org/university-of-toronto-rct-study/
Boaler, J. (2016). Mathematical mindsets: Unleashing students' potential through creative math, inspiring messages and innovative teaching. John Wiley & Sons.
Broadbent, J., & Poon, W. L. (2015). Self-regulated learning strategies & academic achievement in online higher education learning environments: A systematic review. The Internet and Higher Education, 27, 1–13. https://doi.org/10.1016/j.iheduc.2015.04.007
Brown, J., & Wilson, K. (2015). The impact of educational playlists on mathematical problem-solving skills. Educational Research and Reviews, 10(15), 2045–2053.
Cepeda, N. J., Pashler, H., Vul, E., Wixted, J. T., & Rohrer, D. (2006). Distributed practice in verbal recall tasks: A review and quantitative synthesis. Psychological Bulletin, 132(3), 354–380. https://doi.org/10.1037/0033-2909.132.3.354
Cheng, M., & Mayes, R. (2018). Supporting self-directed learning in mathematics: A review of recent research. Journal of Mathematics Education, 11(1), 45–63.
Clark, L., & Smith, A. (2021). Bridging the achievement gap with educational playlists: A study on equity in mathematics education. Journal of Equity in Education, 12(1), 45–61.
Cruz, L. J. (2022). YouTube-based teacher-created videos for online mathematics learning amidst the COVID-19 pandemic. Webology, 19(2), 109–120.
Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. Plenum Press.
Education Week. (2017, November 7). The case(s) against personalized learning. https://www.edweek.org/technology/the-case-s-against-personalized-learning/2017/11
EdSurge. (2017, November 6). Playlists alone don’t equal personalized learning. https://www.edsurge.com/news/2017-11-06-playlists-alone-don-t-equal-personalized-learning
Facer, K., & Selwyn, N. (2019). Using curated digital content to enhance learning in STEM education. Journal of Educational Multimedia and Hypermedia, 28(1), 75–88.
Gilas, D. B., & Feliciano, E. J. (2022). YouTube video playlist as mathematics supplementary learning material for blended learning. European Journal of Interactive Multimedia and Education, 3(2), 1–10.
Green, P., & Thomas, M. (2017). Multimedia learning in mathematics: Enhancing student understanding of combinatorial concepts. International Journal of Educational Technology in Higher Education, 14(1), 25.
Harris, D., & Jones, L. (2019). The role of teacher facilitation in the effective use of educational playlists. Journal of Instructional Pedagogies, 21, 1–12.
Herold, B. (2016, June 3). The case(s) for and against online playlists in education. Education Week. https://www.edweek.org/technology/the-case-s-for-and-against-online-playlists-in-education/2016/06
Hiebert, J., & Grouws, D. A. (2007). The effects of classroom mathematics teaching on students' learning. In F. K. Lester Jr. (Ed.), Second handbook of research on mathematics teaching and learning (pp. 371–404). Information Age Publishing.
Horn, M. B., & Staker, H. (2015). Blended: Using disruptive innovation to improve schools. Jossey-Bass.
Insorio, A. O. (2022). YouTube video playlist as mathematics supplementary learning material for blended learning [Action research report]. Zenodo. https://doi.org/10.5281/zenodo.7424762
Johnson, L., & Marsh, K. (2017). A comparative analysis of traditional instruction versus technology-enhanced learning in teaching combinatorics. Journal of Mathematical Education, 43(4), 289–304.
Kay, R. H., & LeSage, A. (2009). Examining the benefits and challenges of using audience response systems: A review of the literature. Computers & Education, 53(3), 819–827. https://doi.org/10.1016/j.compedu.2009.05.001
Lee, H., & Martin, C. (2018). Integrating educational playlists into the flipped classroom model: Enhancing learning outcomes in mathematics. Journal of Interactive Learning Research, 29(2), 231–246.
Liu, Y., & Zhang, W. (2020). Facilitating collaborative learning in mathematics through educational playlists. Journal of Educational Technology Development and Exchange, 13(2), 145–161.
Mayer, R. E. (2009). Multimedia learning (2nd ed.). Cambridge University Press.
Means, B., Toyama, Y., Murphy, R., Bakia, M., & Jones, K. (2009). Evaluation of evidence-based practices in online learning: A meta-analysis and review of online learning studies. U.S. Department of Education.
Miller, S., & Johnson, T. (2018). The effects of spaced repetition on long-term retention in learning combinatorics through educational playlists. Educational Psychology Review, 30(2), 411–429.
Nguyen, T., & Pham, L. (2021). Fostering independent learning skills through technology: The role of educational playlists in secondary education. Journal of Educational Research and Practice, 11(3), 200–215.
Novak Education. (2025, March 6). Personalize learning with playlists: A teacher’s guide. https://www.novakeducation.com/blog/personalize-learning-with-playlists
Panadero, E., & Broadbent, J. (2018). Developing evaluative judgement: A self-regulated learning perspective. In D. Boud, R. Ajjawi, P. Dawson, & J. Tai (Eds.), Developing evaluative judgement in higher education: Assessment for knowing and producing quality work (pp. 80–89). Routledge.
Pape, S. J., & Tchoshanov, M. A. (2001). The role of technology in mathematics education: A survey of recent research. Journal for Research in Mathematics Education, 32(1), 112–136.
Park, J.-H., & Choi, H. J. (2009). Factors influencing adult learners' decision to drop out or persist in online learning. Educational Technology & Society, 12(4), 207–217.
Piaget, J. (1970). Psychology and pedagogy. Viking Press.
PowerMyLearning. (2023). Family Playlists: Evidence base. https://powermylearning.org/family-playlists/
Rivers, N., & Wells, D. (2016). Reducing math anxiety through self-paced learning: The impact of educational playlists on student confidence and performance. Journal of Educational Psychology, 108(3), 457–468.
Selden, A., & Selden, J. (2014). Mathematics content for elementary teachers. Cengage Learning.
Smith, J., & Randall, M. (2016). The benefits of personalized learning in mathematics education: A case study on combinatorics. Mathematics Education Research Journal, 28(1), 53–67.
SRI Education. (2014). Research on the use of Khan Academy in schools: Implementation briefing. SRI International. https://www.sri.com/publication/research-on-the-use-of-khan-academy-in-schools/
Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285. https://doi.org/10.1207/s15516709cog1202_4
Tomlinson, C. A., & Moon, T. R. (2013). Differentiated instruction in mathematics: Research-based strategies to meet the diverse needs of all learners. Corwin Press.
Tucker, A. (2002). Applied combinatorics (5th ed.). Wiley.
Van Dijk, J. (2020). The digital divide. Polity.
Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.
Walkington, C. (2013). Using adaptive learning technologies to personalize instruction to student interests: The impact of relevant contexts on performance and learning outcomes. Journal of Educational Psychology, 105(4), 932–945. https://doi.org/10.1037/a0031882
Wang, M., Shen, R., Novak, D., & Pan, X. (2013). The impact of mobile learning on students' learning behaviors and performance: Report from a large blended classroom. British Journal of Educational Technology, 44(4), 592–606.
Weatherholtz, K., & Yamkovenko, B. (2023, May 11). Every minute spent on Khan Academy can lead to learning gains. Khan Academy. https://blog.khanacademy.org/every-minute-on-khan-academy/