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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
A. Rehmani, Teacher education in Pakistan with particular reference to teachers’ conceptions of teaching. (2006)
M. Fullan, Stratosphere. (Pearson, 2013)
C.A. Tomlinson, How to differentiate instruction in mixed-ability classrooms? ASCD (2001)
W. Powell, O. Kusuma-Powell, How to teach now: five keys to personalized learning in the global classroom. ASCD (2011)
C. Walkington, M.L. Bernacki, Appraising research on personalized learning: definitions, theoretical alignment, advancements, and future directions. (2020)
V. Frunză, C. Petre, Obstacles in learning’s differentiation and individualization on primary school. Procedia Soc. Behav. Sci. 180, 573–579 (2015)
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)
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)
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)
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)
K. Park, H. Ji, H. Lim, Development of a learner profiling system using multidimensional characteristics analysis. Math. Probl. Eng. 2015
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)
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)
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)
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)
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)
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
R.M. Felder, R. Brent, Understanding student differences. J. Eng. Educ. 94(1), 57–72 (2005)
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)
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)
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)
M. Spratt, How good are we at knowing what learners like? System 27(2), 141–155 (1999)
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)
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)
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)
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)
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)
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)
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)
M.S. Zywno, Instructional technology, learning styles and academic achievement. Age 7(1) (2002)
T.F. Hawk, A.J. Shah, Using learning style instruments to enhance student learning. Decis. Sci. J. Innov. Educ. 5(1), 1–19 (2007)
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)
P.M. Newton, M. Miah, Evidence-based higher education–is the learning styles ‘myth’ important? Front. Psychol. 8, 444 (2017)
R.M. Felder, J. Spurlin, Applications, reliability and validity of the index of learning styles. Int. J. Eng. Educ. 21(1), 103–112 (2005)
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)
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)
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
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)
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)
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)
T.P. O’Brien, Construct validation of the gregorc style delineator: an application of LISREL 7. Educ. Psychol. Measur. 50(3), 631–636 (1990)
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)
F. Coffield, D. Moseley, E. Hall, K. Ecclestone, Learning styles and pedagogy in post-16 learning: a systematic and critical review. (2004)
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)
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)
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)
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)
J.L. Meece, E.M. Anderman, L.H. Anderman, Classroom goal structure, student motivation, and academic achievement. Annu. Rev. Psychol. 57, 487–503 (2006)
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)
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)
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
P.R. Pintrich, A manual for the use of the Motivated Strategies for Learning Questionnaire (MSLQ). (1991)
L.R. Gay, G.E. Mills, P.W. Airasian, Educational research: competencies for analysis and applications, student, value edn. (Merrill, Pearson, NJ, 2012)
J. Hair, R. Anderson, R.L. Tatham, W.C. Black, Multivariate data analysis, 4th edn. (Prentice-Hall In, New jersey, 1995)
A. Shah, Teaching of urdu: problems and prospects, in International Multilingual Conference Ethiraj Collage for women Chennai, (Ethiraj Collage for Women, Chennai, 2016)
X. Ma, J. Xu, The causal ordering of mathematics anxiety and mathematics achievement: a longitudinal panel analysis. J. Adolesc. 27(2), 165–179 (2004)
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)
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)
M. Gall, W. Borg, J. Gall, Educational research: an introduction, 6th edn. (Longman, White Plains, NY, 1996)
J.W. Creswell, Educational research: planning, conducting, and evaluating quantitative (Prentice Hall, Upper Saddle River, NJ, 2002), pp. 146–166
T.H. Eysink, M. Hulsbeek, H. Gijlers, Supporting primary school teachers in differentiating in the regular classroom. Teach. Teach. Educ. 66, 107–116 (2017)
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)
M. Smith, S. Bourke, Teacher stress: Examining a model based on context, workload, and satisfaction. Teach. Teach. Educ. 8(1), 31–46 (1992)
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
A. Harris, J. Goodall, Do parents know they matter? Engaging all parents in learning. Educ. Res. 50(3), 277–289 (2008)
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)
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)
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
W.Q. Oga-Baldwin, L.K. Fryer, Profiles of language learning motivation: are new and own languages different? Learn. Indiv. Differ. 79, 101852 (2020)
NEMIS, Pakistan Education Statistics 2016–2017, (2018)
J. Pallant, SPSS survival manual. (McGraw-Hill Education, UK, 2013)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this chapter
Cite this chapter
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
Download citation
DOI: https://doi.org/10.1007/978-3-031-04662-9_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-04661-2
Online ISBN: 978-3-031-04662-9
eBook Packages: EducationEducation (R0)