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Impact of Lesson Planning on Students’ Achievement Using Learner Profile System

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Handbook on Intelligent Techniques in the Educational Process

Abstract

This study proposed and evaluated a Learner Profile System (LPS), which is a web-based solution to generate multiple types of learner profiles. The contents of the profiles include the basic information about the learners, such as, demographics, preference profile, interest profile, learning styles (LS), and motivational goal orientation (MGO). The pilot study of the instrument, a specifically designed Student Survey (SS) for the LPS, was conducted on the middle school students (N = 60) to measure the construct validity and reliability. The internal consistency reliability of the MGO across two motivational aspects was 0.6530, and the exploratory factor analysis revealed four components. Afterwards, an experimental study was done on the middle school students (N = 307), in order to examine the impact of LPS on learners’ achievement. To supplement the above data, semi-structured interviews were conducted to explore teachers’ perception and their perspective regarding the feasibility and use of the LPS. The analysis of the results showed that the group which learned using the LPS demonstrated significant improvement in their assessment scores in comparison to the controlled group. This study supported the hypothesis of a positive impact on learners’ achievement through the use of personalized learning profiles.

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References

  1. A. Rehmani, Teacher education in Pakistan with particular reference to teachers’ conceptions of teaching. (2006)

    Google Scholar 

  2. M. Fullan, Stratosphere. (Pearson, 2013)

    Google Scholar 

  3. C.A. Tomlinson, How to differentiate instruction in mixed-ability classrooms? ASCD (2001)

    Google Scholar 

  4. W. Powell, O. Kusuma-Powell, How to teach now: five keys to personalized learning in the global classroom. ASCD (2011)

    Google Scholar 

  5. C. Walkington, M.L. Bernacki, Appraising research on personalized learning: definitions, theoretical alignment, advancements, and future directions. (2020)

    Google Scholar 

  6. V. Frunză, C. Petre, Obstacles in learning’s differentiation and individualization on primary school. Procedia Soc. Behav. Sci. 180, 573–579 (2015)

    Article  Google Scholar 

  7. M. Chamberlin, R. Powers, The promise of differentiated instruction for enhancing the mathematical understandings of college students. Teach. Math. Appl. Int. J. IMA 29(3), 113–139 (2010)

    Google Scholar 

  8. S. Valiandes, Evaluating the impact of differentiated instruction on literacy and reading in mixed ability classrooms: quality and equity dimensions of education effectiveness. Stud. Educ. Eval. 45, 17–26 (2015)

    Article  Google Scholar 

  9. P. Alavinia, S. Farhady, Using differentiated instruction to teach vocabulary in mixed ability classes with a focus on multiple intelligences and learning styles. Int. J. Appl. 2(4), 72–79 (2012)

    Google Scholar 

  10. M. Aliakbari, J.K. Haghighi, On the effectiveness of differentiated instruction in the enhancement of Iranian learners reading comprehension in separate gender education. Proc. Soc. Behav. Sci. 98, 182–189 (2014)

    Article  Google Scholar 

  11. K. Park, H. Ji, H. Lim, Development of a learner profiling system using multidimensional characteristics analysis. Math. Probl. Eng. 2015

    Google Scholar 

  12. M.W. Smith, J.D. Wilhelm, Reading don't fix no chevys: literacy in the lives of young men. (Heinemann, 361 Hanover Street, Portsmouth, NH 03801–3912, 2002)

    Google Scholar 

  13. Y.L. Wang, J.C. Liang, C.Y. Lin, C.C. Tsai, Identifying Taiwanese junior-high school students’ mathematics learning profiles and their roles in mathematics learning self-efficacy and academic performance. Learn. Individ. Differ. 54, 92–101 (2017)

    Article  Google Scholar 

  14. P. Den Brok, S. Telli, J. Cakiroglu, R. Taconis, C. Tekkaya, Learning environment profiles of Turkish secondary biology classrooms. Learn. Environ. Res. 13(3), 187–204 (2010)

    Article  Google Scholar 

  15. P. Lalos, S. Retalis, Y. Psaromiligkos, Creating personalised quizzes both to the learner and to the access device characteristics: the Case of CosyQTI. in 3rd International Workshop on Authoring of Adaptive and Adaptable Educational Hypermedia (A3EH) (2005)

    Google Scholar 

  16. F. Lazarinis, A service-oriented Web application for learner knowledge representation, management and sharing conforming to IMS LIP. Educ. Inf. Technol. 19(2), 327–344 (2014)

    Article  Google Scholar 

  17. T. Ramandalahy, P. Vidal, J. Broisin, Opening learner profiles across heterogeneous applications, in ICALT 2009. Ninth IEEE International Conference on IEEE Advanced Learning Technologies. (2009), pp. 504–508

    Google Scholar 

  18. R.M. Felder, R. Brent, Understanding student differences. J. Eng. Educ. 94(1), 57–72 (2005)

    Article  Google Scholar 

  19. M. Baeten, E. Kyndt, K. Struyven, F. Dochy, Using student-centred learning environments to stimulate deep approaches to learning: factors encouraging or discouraging their effectiveness. Educ. Res. Rev. 5(3), 243–260 (2010)

    Article  Google Scholar 

  20. J. Jerrard, What does “quality” look like for post-2015 education provision in low-income countries? An exploration of stakeholders’ perspectives of school benefits in village LEAP schools, rural Sindh, Pakistan. Int. J. Educ. Dev. 46, 82–93 (2016)

    Article  Google Scholar 

  21. J. Decristan, B. Fauth, M. Kunter, G. Büttner, E. Klieme, The interplay between class heterogeneity and teaching quality in primary school. Int. J. Educ. Res. 86, 109–121 (2017)

    Article  Google Scholar 

  22. M. Spratt, How good are we at knowing what learners like? System 27(2), 141–155 (1999)

    Article  Google Scholar 

  23. A.O. Awofala, A.O. Lawani, Increasing mathematics achievement of senior secondary school students through differentiated instruction. J. Educ. Sci. 4(1), 1–19 (2020)

    Google Scholar 

  24. C.R. Ellerbock, S.M. Kiefer, Fostering an adolescent-centered community responsive to student needs: lessons learned and suggestions for middle level educators. Clear. House J. Educ. Strat. Issues Ideas 87(6), 229–235 (2014)

    Article  Google Scholar 

  25. C. Hulme, M.J. Snowling, G. West, A. Lervåg, M. Melby-Lervåg, Children’s language skills can be improved: lessons from psychological science for educational policy. Curr. Dir. Psychol. Sci. 29(4), 372–377 (2020)

    Article  Google Scholar 

  26. N.B. Ishak, M.M. Awang, The relationship of student learning styles and achievement in history subject. Int. J. Soc. Sci. Human. Invent. 4(3), 3372–3377 (2017)

    Google Scholar 

  27. S. Damrongpanit, A. Reungtragul, Matching of learning styles and teaching styles: advantage and disadvantage on ninth-grade students’ academic achievements. Educ. Res. Rev. 8(20), 1937–1947 (2013)

    Google Scholar 

  28. M.Z. Ghani, R.A. Wahab, W.S.M. Zain, Dominance learning styles on ADHD student learning behaviors in secondary school. Glob. J. Interdiscipl. Soc. Sci. 3(3), 133–139 (2014)

    Google Scholar 

  29. T.G. Lynch, N.N. Woelfl, D.J. Steele, C.S. Hanssen, Learning style influences student examination performance. Am. J. Surg. 176(1), 62–66 (1998)

    Article  Google Scholar 

  30. M.S. Zywno, Instructional technology, learning styles and academic achievement. Age 7(1) (2002)

    Google Scholar 

  31. T.F. Hawk, A.J. Shah, Using learning style instruments to enhance student learning. Decis. Sci. J. Innov. Educ. 5(1), 1–19 (2007)

    Article  Google Scholar 

  32. S. Avsec, A. Szewczyk-Zakrzewska, Predicting academic success and technological literacy in secondary education: a learning styles perspective. Int. J. Technol. Des. Educ. 27(2), 233–250 (2017)

    Article  Google Scholar 

  33. P.M. Newton, M. Miah, Evidence-based higher education–is the learning styles ‘myth’ important? Front. Psychol. 8, 444 (2017)

    Article  Google Scholar 

  34. R.M. Felder, J. Spurlin, Applications, reliability and validity of the index of learning styles. Int. J. Eng. Educ. 21(1), 103–112 (2005)

    Google Scholar 

  35. C.C. Hosford, W.A. Siders, Felder-Soloman’s index of learning styles: Internal consistency, temporal stability, and factor structure. Teach. Learn. Med. 22(4), 298–303 (2010)

    Article  Google Scholar 

  36. T.A. Litzinger, S.H. Lee, J.C. Wise, R.M. Felder, A psychometric study of the index of learning styles©. J. Eng. Educ. 96(4), 309–319 (2007)

    Article  Google Scholar 

  37. J. Wang, T. Mendori, A study of the reliability and validity of felder-soloman index of learning styles in mandarin version, in 2015 IIAI 4th International Congress on Advanced Applied Informatics (IIAI-AAI), (2015), pp. 370–373

    Google Scholar 

  38. F. Vizeshfar, C. Torabizadeh, The effect of teaching based on dominant learning style on nursing students’ academic achievement. Nurse Educ. Pract. 28, 103–108 (2018)

    Article  Google Scholar 

  39. C. Manolis, D.J. Burns, R. Assudani, R. Chinta, Assessing experiential learning styles: a methodological reconstruction and validation of the Kolb Learning Style Inventory. Learn. Individ. Differ. 23, 44–52 (2013)

    Article  Google Scholar 

  40. J.L. Ross, M.T. Drysdale, R.A. Schulz, Cognitive learning styles and academic performance in two postsecondary computer application courses. J. Res. Comput. Educ. 33(4), 400–412 (2001)

    Article  Google Scholar 

  41. T.P. O’Brien, Construct validation of the gregorc style delineator: an application of LISREL 7. Educ. Psychol. Measur. 50(3), 631–636 (1990)

    Article  Google Scholar 

  42. T.G. Reio Jr., A.K. Wiswell, An examination of the factor structure and construct validity of the gregorc style delineator. Educ. Psychol. Measur. 66(3), 489–501 (2006)

    Article  MathSciNet  Google Scholar 

  43. F. Coffield, D. Moseley, E. Hall, K. Ecclestone, Learning styles and pedagogy in post-16 learning: a systematic and critical review. (2004)

    Google Scholar 

  44. N. Fang, M.F. bin Daud, S.A. Al Haddad, K. Mohd-Yusof, A quantitative investigation of learning styles, motivation and learning strategies for undergraduate engineering students. Global J. Eng. Educ. 19(1) (2017)

    Google Scholar 

  45. J.L. Meece, P. Herman, B.L. McCombs, Relations of learner-centered teaching practices to adolescents’ achievement goals. Int. J. Educ. Res. 39(4–5), 457–475 (2003)

    Article  Google Scholar 

  46. C.A. Wolters, M.B. Benzon, Assessing and predicting college students’ use of strategies for the self-regulation of motivation. J. Exp. Educ. 81(2), 199–221 (2013)

    Article  Google Scholar 

  47. A. El-Adl, H. Alkharusi, Relationships between self-regulated learning strategies, learning motivation and mathematics achievement. Cypriot J. Educ. Sci. 15(1), 104–111 (2020)

    Article  Google Scholar 

  48. J.L. Meece, E.M. Anderman, L.H. Anderman, Classroom goal structure, student motivation, and academic achievement. Annu. Rev. Psychol. 57, 487–503 (2006)

    Article  Google Scholar 

  49. B.L. Ng, W.C. Liu, J.C. Wang, Student motivation and learning in mathematics and science: a cluster analysis. Int. J. Sci. Math. Educ. 14(7), 1359–1376 (2016)

    Article  Google Scholar 

  50. B. Rawat, S.K. Dwivedi, Discovering learners’ characteristics through cluster analysis for recommendation of courses in E-learning environment. Int. J. Inform. Commun. Technol. Educ. (IJICTE) 15(1), 42–66 (2019)

    Article  Google Scholar 

  51. B.A. Soloman, R.M. Felder, Index of learning styles questionnaire. NC State University (2005). http://www.engr.ncsu.edu/learningstyles/ilsweb.html. Accessed 14 May 2010

  52. P.R. Pintrich, A manual for the use of the Motivated Strategies for Learning Questionnaire (MSLQ). (1991)

    Google Scholar 

  53. L.R. Gay, G.E. Mills, P.W. Airasian, Educational research: competencies for analysis and applications, student, value edn. (Merrill, Pearson, NJ, 2012)

    Google Scholar 

  54. J. Hair, R. Anderson, R.L. Tatham, W.C. Black, Multivariate data analysis, 4th edn. (Prentice-Hall In, New jersey, 1995)

    Google Scholar 

  55. A. Shah, Teaching of urdu: problems and prospects, in International Multilingual Conference Ethiraj Collage for women Chennai, (Ethiraj Collage for Women, Chennai, 2016)

    Google Scholar 

  56. X. Ma, J. Xu, The causal ordering of mathematics anxiety and mathematics achievement: a longitudinal panel analysis. J. Adolesc. 27(2), 165–179 (2004)

    Article  Google Scholar 

  57. E. Zakaria, N.M. Nordin, The effects of mathematics anxiety on matriculation students as related to motivation and achievement. Eurasia J. Math. Sci. Technol. Educ. 4(1) (2008)

    Google Scholar 

  58. N. Berger, E. Mackenzie, K. Holmes, Positive attitudes towards mathematics and science are mutually beneficial for student achievement: a latent profile analysis of TIMSS 2015. Austr. Educ. Res. 1–36 (2020)

    Google Scholar 

  59. M. Gall, W. Borg, J. Gall, Educational research: an introduction, 6th edn. (Longman, White Plains, NY, 1996)

    Google Scholar 

  60. J.W. Creswell, Educational research: planning, conducting, and evaluating quantitative (Prentice Hall, Upper Saddle River, NJ, 2002), pp. 146–166

    Google Scholar 

  61. T.H. Eysink, M. Hulsbeek, H. Gijlers, Supporting primary school teachers in differentiating in the regular classroom. Teach. Teach. Educ. 66, 107–116 (2017)

    Article  Google Scholar 

  62. M. Inguva, V. Tuzlukova, P. Sancheti, Foundation program english language learner profile: a case study in Oman. J. Lang. Teach. Res. 10(6), 1251–1256 (2019)

    Article  Google Scholar 

  63. M. Smith, S. Bourke, Teacher stress: Examining a model based on context, workload, and satisfaction. Teach. Teach. Educ. 8(1), 31–46 (1992)

    Article  Google Scholar 

  64. R. Koper, Use of the semantic web to solve some basic problems in education: increase flexible, distributed lifelong learning; decrease teacher's workload. J. Interact. Media Educ. 2004(1), 2004

    Google Scholar 

  65. A. Harris, J. Goodall, Do parents know they matter? Engaging all parents in learning. Educ. Res. 50(3), 277–289 (2008)

    Article  Google Scholar 

  66. N. Yazdani, K.L. Siedlecki, Z. Cao, H. Cham, Longitudinal impact of sociocultural factors and parent beliefs on parent-teacher relationship strength. Element. Schl. J. 121(1), 1–33 (2020)

    Google Scholar 

  67. J.M. Faber, C.A. Glas, A.J. Visscher, Differentiated instruction in a data-based decision-making context. Sch. Eff. Sch. Improv. 29(1), 43–63 (2018)

    Article  Google Scholar 

  68. J.M. Morse, Pragmatic threads in mixed methods research design, in Handbook of Mixed Methods in Social and Behavioral Research, eds. by A. Tashakkori, C. Teddlie. (Sage, Thousand Oaks, CA, 2003), pp.189–208

    Google Scholar 

  69. W.Q. Oga-Baldwin, L.K. Fryer, Profiles of language learning motivation: are new and own languages different? Learn. Indiv. Differ. 79, 101852 (2020)

    Google Scholar 

  70. NEMIS, Pakistan Education Statistics 2016–2017, (2018)

    Google Scholar 

  71. J. Pallant, SPSS survival manual. (McGraw-Hill Education, UK, 2013)

    Google Scholar 

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Mirza, M.A., Khurshid, K., Shah, Z., Shah, F., Levula, A., Klašnja-Milićević, A. (2022). Impact of Lesson Planning on Students’ Achievement Using Learner Profile System. In: Ivanović, M., Klašnja-Milićević, A., Jain, L.C. (eds) Handbook on Intelligent Techniques in the Educational Process. Learning and Analytics in Intelligent Systems, vol 29. Springer, Cham. https://doi.org/10.1007/978-3-031-04662-9_7

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