Eurasia Journal of Mathematics, Science and Technology Education

• Afthanorhan, W. M. A. B. W., & Ahmad, S. (2014). Path analysis in covariance-based structural equation modeling with Amos 18.0. European Journal of Business and Social Sciences, 3(2), 59-68. http://www.ejbss.com/recent.aspx
• Ainley, M., & Hidi, S. (2014). Interest and enjoyment in learning. In R. Pekrun, & L. Linnenbrink-Garcia (Eds.), International handbook of emotions in education (pp. 120-135). Routledge. https://doi.org/10.4324/9780203148211
• Alegre, F., Moliner, L., Maroto, A., & Lorenzo-Valentin, G. (2019). Peer tutoring and mathematics in secondary education: Literature review, effect sizes, moderators, and implications for practice. Heliyon, 5(9), Article e02491. https://doi.org/10.1177/0022057418800950
• Ary, D., Jacobs, L. C., & Razavieh, A. (1972). Introduction to research in education. Holt, Rinehart & Winston.
• Arthur, Y. D., Boadu, S. K., & Asare, B. (2022). Effects of peer tutoring, teaching quality and motivation on mathematics achievement in senior high schools. International Journal of Educational Sciences, 37(3), 35-43. https://doi.org/10.31901/24566322.2022/37.1-3.1221
• Bamfo, B. A., Dogbe, C. S. K., & Mingle, H. (2018). Abusive customer behavior and frontline employee turnover intentions in the banking industry: The mediating role of employee satisfaction. Cogent Business and Management, 5(1), Article 1522753. https://doi.org/10.1080/23311975.2018.1522753
• Bernard, H. R. (2006). Research methods in anthropology: Qualitative and quantitative approaches. Altamira Press.
• Boadu, S. K., Arthur, Y. D., & Bonyah, E. (2023). Mediation and moderation effects of motivation and teaching quality on the relationship between peer tutoring and mathematics achievement. Journal of Mathematics and Science Teacher, 3(2), Article em039. https://doi.org/10.29333/mathsciteacher/13166
• Bornmann, L., Marx, W., Schier, H., Rahm, E., Thor, A., & Daniel, H. D. (2009). Convergent validity of bibliometric Google Scholar data in the field of chemistry–Citation counts for papers that were accepted by Angewandte Chemie International Edition or rejected but published elsewhere, using Google Scholar, Science Citation Index, Scopus, and Chemical Abstracts. Journal of Informetrics, 3(1), 27-35. https://doi.org/10.1016/j.joi.2008.11.001
• Boswell, M. L. (2024). A quasi-experimental study on the effectiveness of a supplemental digital mathematics tool in grade 9 mathematics [Doctoral dissertation, National University].
• Carlson, K. D., & Herdman, A. O. (2012). Understanding the impact of convergent validity on research results. Organizational Research Methods, 15(1), 17-32. https://doi.org/10.1177/1094428110392383
• Chen, P. (2011). From CMS to SNA: Educational networking for urban teachers. Journal of Urban Learning, Teaching, and Research, 7, 50-61.
• Deci, E. L., & Ryan, R. M. (2000). The “what” and “why” of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11(4), 227-268. https://doi.org/10.1207/S15327965PLI1104_01
• Dillenbourg, P. (1999). What do you mean by collaborative learning? In P. Dillenbourg (Ed.), Collaborative-learning: Cognitive and computational approaches (pp. 1-19). Elsevier. https://telearn.hal.science/hal-00190240v1
• Dogbe, C. S. K., Tian, H., Pomegbe, W. W. K., Sarsah, S. A., & Otoo, C. O. A. (2020). Effect of network embeddedness on innovation performance of small and medium-sized enterprises. Journal of Strategy and Management, 13(2), 181-197. https://doi.org/10.1108/JSMA-07-2019-0126
• Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. https://doi.org/10.2307/3151312
• Froiland, J. M., & Davison, M. L. (2016). The longitudinal influences of peers, parents, motivation, and mathematics course-taking on high school math achievement. Learning and Individual Differences, 50, 252-259. https://doi.org/10.1016/j.lindif.2016.07.012
• Ginsburg-Block, M. D., Rohrbeck, C. A., & Fantuzzo, J. W. (2006). A meta-analytic review of social, self-concept, and behavioral outcomes of peer-assisted learning. Journal of Educational Psychology, 98(4), 732-749. https://doi.org/10.1037/0022-0663.98.4. 732
• Habók, A., Magyar, A., Németh, M. B., & Csapó, B. (2020). Motivation and self-related beliefs as predictors of academic achievement in reading and mathematics: Structural equation models of longitudinal data. International Journal of Educational Research, 103, Article 101634. https://doi.org/10.1016/j.ijer.2020.101634
• Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis (7th ed.). Prentice Hall. https://www.pearson.com/uk/educators/higher-education_educators/program/Hair-Multivariate-Data_Analysis-Global-Edition-7th_Edition/PGM916641.html
• Harackiewicz, J. M., Smith, J. L., & Priniski, S. J. (2016). Interest matters: The importance of promoting interest in education. Policy Insights from the Behavioral and Brain Sciences, 3(2), 220-227. https://doi.org/10.1177/2372732216655542
• Haviz, M., & Maris, I. (2020). Measuring mathematics and science teachers’ perception on thinking and acting in 21st-century learning. Journal for the Education of Gifted Young Scientists, 8(4), 1319-1328. https://doi.org/10.17478/jegys.747395
• Hegedus, S., Moreno-Armella, L., & Schukajlow, S. (2019). Technology integration in mathematics education. In L. D. English, & D. Kirshner (Eds.), Handbook of international research in mathematics education (3rd ed., pp. 583-609). Routledge. https://doi.org/10.4324/9780203448946
• Hidi, S., & Renninger, K. A. (2006). The four-phase model of interest development. Educational Psychologist, 41(2), 111-127. https://doi.org/10.1207/s15326985ep4102_4
• Johnson, D. W., Johnson, R. T., & Smith, K. A. (2007). The state of cooperative learning in postsecondary and professional settings. Educational Psychology Review, 19(1), 15-29. https://doi.org/10.1007/s10648-006-9038-8
• Johnson, D. W., Johnson, R. T., & Smith, K. A. (2014). Cooperative learning: Improving university instruction by basing practice on validated theory. Journal on Excellence in College Teaching, 25(3&4), 85-118.
• Johnson, D.W., Johnson, R., & Smith, K. A. (1998). Active learning: Cooperative in the college classroom. Interaction Book Company.
• Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist, 41(2), 75-86. https://doi.org/10.1207/s15326985ep4102_1
• Kline, R. B. (2011). Convergence of structural equation modeling and multilevel modeling. In M. Willams, & W. P. Vogt (Eds.), The SAGE handbook of innovation in social research methods (pp. 562-289). SAGE. https://doi.org/10.4135/9781446268261.n31
• Korhonen, J., Tapola, A., Linnanmäki, K., & Aunio, P. (2016). Gendered pathways to educational aspirations: The role of academic self-concept, school burnout, achievement and interest in mathematics and reading. Learning and Instruction, 46, 21-33. https://doi.org/10.1016/j.learninstruc. 2016.08.006
• Lahey, B. B., McNealy, K., Knodt, A., Zald, D. H., Sporns, O., Manuck, S. B., Flory, J. D., Applegate, B., Rathouz, P. J., & Hariri, A. R. (2012). Using confirmatory factor analysis to measure contemporaneous activation of defined neuronal networks in functional magnetic resonance imaging. Neuroimage, 60(4), 1982-1991. https://doi.org/10.1016/j.neuroimage.2012.02.002
• Lerkkanen, M. K., Kiuru, N., Pakarinen, E., Viljaranta, J., Poikkeus, A. M., Rasku-Puttonen, H., Siekkinen, M., & Nurmi, J. E. (2012). The role of teaching practices in the development of children’s interest in reading and mathematics in kindergarten. Contemporary Educational Psychology, 37(4), 266-279. https://doi.org/10.1016/j.cedpsych.2011.03.004
• Li, L., Peng, Z., Lu, L., Liao, H., & Li, H. (2020). Peer relationships, self-efficacy, academic motivation, and performance in mathematics in Zhuang adolescents: A moderated mediation model. Children and Youth Services Review, 118, Article 105358. https://doi.org/10.1016/j.childyouth.2020.105358
• Marshall, C., & Rossman, G. B. (2014). Designing qualitative research. Sage publications.
• Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017-1054. https://doi.org/10.1111/j.1467-9620.2006.00684.x
• National Association of Colleges and Employers. (2019). NACE competencies. https://www.naceweb.org/job-market/competencies/nace-competencies/
• National Mathematics Advisory Panel. (2008). Foundations for success: The final report of the National Mathematics Advisory Panel. US Department of Education. https://files.eric.ed.gov/fulltext/ED500486.pdf
• National Research Council. (2012). Education for life and work: Developing transferable knowledge and skills in the 21^st century. National Academies Press.
• Nayebi, H., & Nayebi, H. (2020). Path analysis. In H. Nayebi (Ed.), Advanced statistics for testing assumed causal relationships: Multiple regression analysis path analysis logistic regression analysis (pp. 47-78). Springer. https://doi.org/10.1007/978-3-030-54754-7_2
• Nguyen, T. T. L. (2019). Selection of research paradigms in English language teaching: Personal reflections and future directions. In Proceedings of the AICLL 2019 (pp. 1-19). https://doi.org/10.18502/kss.v3i19.4826
• OECD. (2019). PISA 2018 results (volume VI): Are students ready to thrive in an interconnected world? PISA, OECD Publishing. 20.500.12592/kbsf90.
• Oppong-Gyebi, E., Dissou, Y. A., Brantuo, W. A., Maanu, V., Boateng, F. O., & Adu-Obeng, B. (2023). Improving STEM mathematics achievement through self-efficacy, student perception, and mathematics connection: The mediating role of student interest. Journal of Pedagogical Research, 7(4), 186-202. https://doi.org/10.33902/JPR.202321085
• Penuel, W. R., & Gallagher, D. J. (2017). Creating research practice partnerships in education. Harvard Education Press.
• Pintrich, P. R., & Schunk, D. H. (2002). Motivation in education: Theory, research, and applications (2nd ed.). Merrill. https://lccn.loc.gov/2012031860
• Pitsia, V., Biggart, A., & Karakolidis, A. (2017). The role of students’ self-beliefs, motivation and attitudes in predicting performance in mathematics: A multilevel analysis of the programme for international student assessment data. Learning and Individual Differences, 55, 163-173. https://doi.org/10.1016/j.lindif.2017.03.014
• Prast, E. J., Van de Weijer-Bergsma, E., Miočević, M., Kroesbergen, E. H., & Van Luit, J. E. (2018). Relations between performance in mathematics and motivation in students of diverse achievement levels. Contemporary Educational Psychology, 55, 84-96. https://doi.org/10.1016/j.cedpsych.2018.08.002
• Reeve, J., Lee, W., & Won, S. (2015). Interest as emotion, as affect, as schema. In K. A. Renninger, M. Nieswandt, & S. Hidi (Eds.), Interest in mathematics and science learning (pp. 79-92). American Educational Research Association. https://doi.org/10.3102/978-0-935302-42-4_5
• Renninger, K. A., & Hidi, S. (2016). The power of interest for motivation and engagement. Routledge. https://doi.org/10.4324/9781315771045
• Röllke, K., Maak, A. L., Wenzel, A., & Grotjohann, N. (2020). Experimental workshops in student labs and at school–What influence do location and personality traits have on learners’ motivational variables? Pedagogical Research, 5(1), Article em0050. https://doi.org/10.29333/pr/6338
• Saunders, M., Lewis, P., & Thornhill, A. (2012). Research methods for business students. Pearson Education Ltd., Harlow. https://www.pearson.com/uk/educators/higher-education-educators/product/Saunders-Saunders-Research-Methods-for-Bu-p-6-6th-Edition/9780273750758.html
• Schmid, R. F., Bernard, R. M., Borokhovski, E., Tamim, R. M., Abrami, P. C., Wade, C. A., & Surkes, M. A. (2018). The effects of technology use in postsecondary education: A meta-analysis of classroom applications. Computers & Education, 125, 334-348. https://doi.org/10.1016/j.compedu.2013.11.002
• Schuessler, L. (2020). Teacher perceptions of integrating technology tools [Doctoral dissertation, Walden University].
• Skaalvik, E. M., Federici, R. A., & Klassen, R. M. (2015). Performance in mathematics and self-efficacy: Relations with motivation for mathematics. International Journal of Educational Research, 72, 129- 136. https://doi.org/10.1016/j.ijer.2015.06.008
• Skinner, B. F. (1985). Cognitive science and behaviourism. British Journal of Psychology, 76(3), 291-301. https://doi.org/10.1111/j.2044-8295.1985.tb01953.x
• Slavin, R. E. (2011). Instruction based on cooperative learning. In Handbook of research on learning and instruction (pp. 358-374). https://doi.org/10.4324/9780203839089
• Taber, K. S. (2018). The use of Cronbach’s alpha when developing and reporting research instruments in science education. Research in Science Education, 48(6), 1273-1296. https://doi.org/10.1007/s11165-016-9602-2
• Thurston, A., Roseth, C., Chiang, T. H., Burns, V., & Topping, K. J. (2020). The influence of social relationships on outcomes in mathematics when using peer tutoring in elementary school. International Journal of Educational Research Open, 1, Article 100004. https://doi.org/10.1016/j.ijedro.2020.100004
• Tosto, M. G., Asbury, K., Mazzocco, M. M., Petrill, S. A., & Kovas, Y. (2016). From classroom environment to performance in mathematics: The mediating role of self-perceived ability and subject interest. Learning and Individual Differences, 50, 260-269. https://doi.org/10.1016/j.lindif.2016.07.009
• Trochim, W. M., & Donnelly, J. P. (2001). Research methods knowledge base (vol. 2). Atomic Dog Publishers. https://www.researchgate.net/profile/William Trochim/publication/243783609_The_Research_Methods_Knowledge_Base/links/55db837008aed a199ac6246/The-Research-Methods-Knowledge Base.pdf
• Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.
• Wang, M. T., & Eccles, J. S. (2013). School context, achievement motivation, and academic engagement: A longitudinal study of school engagement using a multidimensional perspective. Learning and Instruction, 28, 12-23. https://doi.org/10.1016/j.learninstruc.2013.04.002
• Wang, X., Li, Y., & Yao, Y. (2021). Exploring the relationship between teachers’ TPACK and students’ collaborative learning in technology-enhanced mathematics instruction. Computers & Education, 165, Article 104134. https://doi.org/10.1016/j.compedu.2021.104134
• Webb, N. M. (2009). The teacher’s role in promoting collaborative dialogue in the classroom. British Journal of Educational Psychology, 79(1), 1-28. https://doi.org/10.1348/000709908X380772
• Wigfield, A., & Eccles, J. S. (2002). Development of achievement motivation. Academic Press.
• Xia, Y., & Yang, Y. (2019). RMSEA, CFI, and TLI in structural equation modeling with ordered categorical data: The story they tell depends on the estimation methods. Behavior Research Methods, 51(1), 409-428. https://doi.org/10.3758/s13428- 018-1055-2
• Young, J., Gorumek, F., & Hamilton, C. (2018). Technology effectiveness in the mathematics classroom: a systematic review of meta-analytic research. Journal of Computers in Education, 5, 133-148. https://doi.org/10.1007/s40692-018-0104-2
• Zhang, D., & Wang, C. (2020). The relationship between mathematics interest and performance in mathematics: Mediating roles of self-efficacy and mathematics anxiety. International Journal of Educational Research, 104, Article 101648. https://doi.org/10.1016/j.ijer.2020.101648
• Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory into Practice, 41(2), 64-70. https://doi.org/10.1207/s15430421tip4102_2

APA

Boadu, S. K., & Boateng, F. O. (2024). Enhancing students’ achievement in mathematics education in the 21^st century through technology integration, collaborative learning, and student motivation: The mediating role of student interest. Eurasia Journal of Mathematics, Science and Technology Education, 20(11), em2534. https://doi.org/10.29333/ejmste/15622

Vancouver

Boadu SK, Boateng FO. Enhancing students’ achievement in mathematics education in the 21^st century through technology integration, collaborative learning, and student motivation: The mediating role of student interest. EURASIA J Math Sci Tech Ed. 2024;20(11):em2534. https://doi.org/10.29333/ejmste/15622

AMA

Boadu SK, Boateng FO. Enhancing students’ achievement in mathematics education in the 21^st century through technology integration, collaborative learning, and student motivation: The mediating role of student interest. EURASIA J Math Sci Tech Ed. 2024;20(11), em2534. https://doi.org/10.29333/ejmste/15622

Chicago

Boadu, Samuel Kwaku, and Francis Ohene Boateng. "Enhancing students’ achievement in mathematics education in the 21^st century through technology integration, collaborative learning, and student motivation: The mediating role of student interest". Eurasia Journal of Mathematics, Science and Technology Education 2024 20 no. 11 (2024): em2534. https://doi.org/10.29333/ejmste/15622

Harvard

Boadu, S. K., and Boateng, F. O. (2024). Enhancing students’ achievement in mathematics education in the 21^st century through technology integration, collaborative learning, and student motivation: The mediating role of student interest. Eurasia Journal of Mathematics, Science and Technology Education, 20(11), em2534. https://doi.org/10.29333/ejmste/15622

MLA

Boadu, Samuel Kwaku et al. "Enhancing students’ achievement in mathematics education in the 21^st century through technology integration, collaborative learning, and student motivation: The mediating role of student interest". Eurasia Journal of Mathematics, Science and Technology Education, vol. 20, no. 11, 2024, em2534. https://doi.org/10.29333/ejmste/15622