What is the impact of e-books on students’ mathematics performance? A qualitative systematic review

Sami Alshehri

Article ID: 2591
Vol 1, Issue 1, 2024

VIEWS - 320 (Abstract) 456 (PDF)

Abstract


This research explores the impact of digital books on student’s performance in mathematics. The theoretical arguments of this research are based on the self-regulated learning theory. To employ the complete research strategy, 65 papers were retrieved in the first round of research, including 30 from Education Resources Information Center (ERIC), 20 from Science Direct, and 15 from Elton B. Stephens CO (EBSCO). Following that, only 40 papers produced findings from the major section screening. The article’s systematic literature review and thematic analysis of the published material resulted in a sample size of 23 articles for this study. A qualitative thematic analysis software, “NVivo 12”, was used to evaluate qualitative data. The findings indicated that motivation, technological advancement, information technology, learning objectives, sources for digital application, challenges of technology, traditional learning style, and visual information have a significant collision with students’ mathematical learning.


Keywords


e-book; mathematics; learning; student performance; self-regulated

Full Text:

PDF


References


1. Suarez MS. and Woudhuysen SH. A Global History, 1st ed. Oxford, United Kingdom: Oxford University Press; 2013.

2. Helsa Y, Kenedi AK. Edmodo-based blended learning media in learning mathematics. Journal of Teaching and Learning in Elementary Education (JTLEE) 2019; 2(2). doi: 10.33578/jtlee.v2i2.7416

3. Dado V, Dapar Z, Idol F, Jandayan C, Niderost N, Mahinay R. Acceptability of E-Books for Academic Use Among Students and Teachers at Mindanao University of Science and Technology. Mindanao University of Science and Technology 2016.

4. Lim BCY, Liu LWL, Chian HC. Investigating the effects of interactive E-Book towards academic achievement. Asian Journal of University Education 2020; 16(3): 78. doi: 10.24191/ajue.v16i3.10272

5. Santoso T, Siswandari S, Sawiji H. The effectiveness of eBook versus printed books in the rural schools in Indonesia at the modern learning era. International Journal of Educational Research 2018; 3(4): 77-84. doi: 10.24331/ijere.453512

6. Ulum H. The effects of online education on academic success: A meta-analysis study. Education and Information Technologies 2021; 27(1): 429-450. doi: 10.1007/s10639-021-10740-8

7. Mudaly V, Fletcher T. The effectiveness of geogebra when teaching linear functions using the iPad. Problems of Education in the 21st Century 2019; 77(1): 55-81. doi: 10.33225/pec/19.77.55

8. Pardede P. Print vs digital reading comprehension in EFL: A literature review. JET (Journal of English Teaching) 2019; 5(2): 77. doi: 10.33541/jet.v5i2.1059

9. Bloom BS. Taxonomy of Educational Objectives, Handbook: The Cognitive Domain. David McKay, New York; 1956.

10. Alshehri S. Effectiveness of E-Book in improving academic performance and attitudes toward mathematics. Journal of Mathematics Education 2021; 4(24): 1-35. doi: 10.21608/armin.2021.163301

11. Jeong H. A comparison of the influence of electronic books and paper books on reading comprehension, eye fatigue, and perception. The Electronic Library 2012; 30(3): 390-408.

12. Chesser WD. The e-textbook revolution. Library Technology Reports 2011; 47(8): 28-40.

13. Al-astal H, Zaydah A. The effectiveness of an E-book on developing mathematical thinking skills and acquisition of mathematical concepts among 5th graders in Gaza. International Journal of Computer Application 2015; 116(21): 23-29. doi: 10.5120/20461-2824

14. Wijaya TT, Zhou Y, Ware A, et al. Improving the creative thinking skills of the next generation of mathematics teachers using dynamic mathematics software. International Journal of Emerging Technologies in Learning (iJET) 2021; 16(13): 212. doi: 10.3991/ijet.v16i13.21535

15. Zou S, Tang J, Pereira J. Integrating hawgent dynamic mathematics software into cone volume geometry learning in Elementary School. Journal of Teaching and Learning in Elementary Education (JTLEE) 2022; 5(1): 1. doi: 10.33578/jtlee.v5i1.7903

16. Hillmayr D, Ziernwald L, Reinhold F, et al. The potential of digital tools to enhance mathematics and science learning in secondary schools: A context-specific meta-analysis. Computers & Education 2020; 153: 103897. doi: 10.1016/j.compedu.2020.103897

17. Berg SA, Hoffmann K, Dawson D. Not on the same page: Undergraduates’ information retrieval in electronic and print books. The Journal of Academic Librarianship 2010; 36(6): 518-525.

18. Woody WD, Daniel DB, Baker CA. E-books or textbooks: Students prefer textbooks. Computers & Education 2010: 55(3); 945-948.

19. Shepperd JA, Grace JL, Koch EJ. Evaluating the electronic textbook: Is it time to dispense with the paper text? Teaching of Psychology 2008; 35(1): 2-5. doi: 10.1080/00986280701818532

20. Wijaya TT, Cao Y, Weinhandl R, et al. A meta-analysis of the effects of E-books on students’ mathematics achievement. Heliyon 2022; 8(6): e09432. doi: 10.1016/j.heliyon.2022.e09432

21. Connell C, Bayliss L, Farmer W. Effects of eBook readers and tablet computers on reading comprehension. International Journal of Instructional Media 2012; 39(2).

22. Korat O. Reading electronic books as support for vocabulary, story comprehension and word reading in kindergarten and first grade. Computers & Education 2010; 55(1); 24–31.

23. Segal-Drori O, Korat O, Shamir A, Klein S. Reading electronic and printed books with and without adult instruction: Effects on emergent reading. Reading and Writing 2010: 23(8); 913-930.

24. Dinsmore DL, Alexander PA, Loughlin SM. Focusing the conceptual lens on metacognition, self-regulation, and self-regulated learning. Educational Psychology Review 2008; 20(4): 391-409. doi: 10.1007/s10648-008-9083-6

25. Zimmerman BJ, Schunk DH. Self-Regulated Learning and Academic Achievement: Theoretical Perspectives. Routledge; 2001.

26. Pintrich PR. The role of goal orientation in self-regulated learning. In: Handbook of Self-Regulation. Academic Press; 2000. pp. 451-502.

27. Paris SG, Paris AH. Classroom applications of research on self-regulated learning. Educational Psychologist 2001; 36(2): 89-101. doi: 10.1207/s15326985ep3602_4

28. Butler DL. Individualizing instruction in self-regulated learning. Theory Into Practice 2002; 41(2): 81-92. doi: 10.1207/s15430421tip4102_4

29. Abdul Karim SK. The effectiveness of individual self-learning computer-simulated and electronic books in the development of innovative thinking among science students in the second year, Faculty of Education, Sultanate of Oman (experimental study). Journal of the Faculty of Education, University of Assiut 2011; 27(2): 79-88.

30. Johnston MP. Secondary data analysis: A method of which the time has come. Qualitative and Quantitative Methods in Libraries 2017; 3(3): 619-626.

31. Booth A, Sutton A, Papaioannou D. Synthesizing and analyzing quantitative studies. In: Systematic Approaches to A Successful Literature Review, 2nd ed. Sage; 2016. pp. 171-214.

32. Del Amo IF, Erkoyuncu JA, Roy R, et al. A systematic review of augmented reality content-related techniques for knowledge transfer in maintenance applications. Computers in Industry 2018; 103: 47-71. doi: 10.1016/j.compind.2018.08.007

33. Gonçalves E, Castro J, Araújo J, et al. A systematic literature review of iStar extensions. Journal of Systems and Software 2018, 137; 1-33. doi: 10.1016/j.jss.2017.11.023

34. Perevochtchikova M, De la Mora-De la Mora G, Hernández Flores JÁ, et al. Systematic review of integrated studies on functional and thematic ecosystem services in Latin America, 1992–2017. Ecosystem Services 2019; 36: 100900. doi: 10.1016/j.ecoser.2019.100900

35. Yang K, Meho LI. Citation analysis: A comparison of Google Scholar, Scopus, and Web of Science. Proceedings of the American Society for Information Science and Technology 2006; 43(1): 1-15. doi: 10.1002/meet.14504301185

36. Martinez-Harms MJ, Bryan BA, Balvanera P, et al. Making decisions for managing ecosystem services. Biological Conservation 2015; 184: 229-238. doi: 10.1016/j.biocon.2015.01.024

37. Mengist W, Soromessa T. Assessment of forest ecosystem service research trends and methodological approaches at global level: A meta-analysis. Environmental Systems Research 2019; 8(1). doi: 10.1186/s40068-019-0150-4

38. McNiff K. What is qualitative research? The NVivo blog. QSR International 2016.

39. Zamawe F. The implication of using NVivo software in qualitative data analysis: Evidence-Based reflections. Malawi Medical Journal 2015; 27(1): 13. doi: 10.4314/mmj.v27i1.4

40. Richards T. An intellectual history of NUD*IST and NVivo. International Journal of Social Research Methodology 2002; 5(3): 199-214. doi: 10.1080/13645570210146267

41. Kopcha TJ. Teachers’ perceptions of the barriers to technology integration and practices with technology under situated professional development. Computers & Education 2012; 59(4): 1109-1121. doi: 10.1016/j.compedu.2012.05.014

42. Groff J, Mouza C. A framework for addressing challenges to classroom technology use. AACE Review (Formerly AACE Journal) 2008; 16(1): 21-46.

43. Losbichler H, Lehner OM. Limits of artificial intelligence in controlling and the ways forward: A call for future accounting research. Journal of Applied Accounting Research 2021; 22(2): 365-382. doi: 10.1108/jaar-10-2020-0207

44. Ali WZW, Bagheri M, Abdullah MCB, et al. Effects of project-based learning strategy on self-directed learning skills of educational technology students. Contemporary Educational Technology 2013; 4(1). doi: 10.30935/cedtech/6089

45. Bienkowski M, Feng M, Means B. Enhancing Teaching and Learning through Educational Data Mining and Learning Analytics: An Issue Brief. Office of Educational Technology, US Department of Education; 2012.

46. Komba W. Increasing education access through open and distance learning in Tanzania: A critical review of approaches and practices. International Journal of Education and Development using ICT 2009; 5(5): 8-21.

47. Saldaña J. The coding manual for qualitative researchers. The Coding Manual for Qualitative Researchers 2021; 1-44.

48. Mortelmans D. Analyzing qualitative data using NVivo. In: The Palgrave Handbook of Methods for Media Policy Research. Palgrave Macmillan, Cham; 2019. pp. 435-450.

49. Braun V, Clarke V. Using thematic analysis in psychology. Qualitative Research in Psychology 2006; 3(2): 77-101. doi: 10.1191/1478088706qp063oa




DOI: https://doi.org/10.24294/olet.v1i1.2591

Refbacks

  • There are currently no refbacks.


License URL: https://creativecommons.org/licenses/by-nc/4.0/

This site is licensed under a Creative Commons Attribution 4.0 International License.