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The Learning Styles Hypothesis is False, but there are Patterns of Student Characteristics that are Useful

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Abstract

The learning styles hypothesis—and particularly the meshing hypothesis—state that learners’ preferences about their preferred modality of learning (i.e., visual, aural, or kinesthetic) predict learning gains on academic tasks. Despite the fact that this hypothesis is not borne out by the scientific evidence available to us, it still remains in widespread classroom use. This article begins by discussing the evidence against learning styles. Second, the article discusses why teachers might continue to believe in and use learning styles in their classroom as well as why essentialist beliefs about learning are not helpful. Finally, 3 variables that do impact student learning—knowledge, strategies, and interest are discussed. Each is defined, their development and measurements are discussed, and finally some instructional examples are given. Replacing the use of learning styles in the classroom with instructional decisions based on the development of knowledge, strategies, and interest can improve student learning outcomes across a wide range of subjects and grade levels.

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... A forwards search of the 12 reports yielded an additional 8 reports. The citations of previous reviews were examined (Pashler et al., 2008;Cuevas, 2015;Aslaksen and Lorås, 2018;Dinsmore et al., 2022), which yielded one more report. This led to a total of 21 reports of 21 independent studies in this meta-analysis. ...
... However, the findings from this meta-analysis indicated a small, but statistically reliable benefit of matching instruction based on learning styles. This aligns with the majority of educators' perspectives (Dekker et al., 2012;Nancekivell et al., 2020;Eitel et al., 2021) but conflicts with the conclusions of previous reviews by educational researchers (Cuevas, 2015;An and Carr, 2017;Aslaksen and Lorås, 2018;Dinsmore et al., 2022;Yan and Fralick, 2022). What distinguishes this meta-analysis from previous reviews is (1) its singular focus on studies comparing instruction matched and unmatched to modality learning styles and (2) its systematic approach to gathering relevant studies and aggregating findings. ...
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Learning styles have been a contentious topic in education for years. The purpose of this study was to conduct a meta-analysis of the effects of matching instruction to modality learning styles compared to unmatched instruction on learning outcomes. A systematic search of the research findings yielded 21 eligible studies with 101 effect sizes and 1,712 participants for the meta-analysis. Based on robust variance estimation, there was an overall benefit of matching instruction to learning styles, g = 0.31, SE = 0.12, 95% CI = [0.05, 0.57], p = 0.02. However, only 26% of learning outcome measures indicated matched instruction benefits for at least two styles, indicating a crossover interaction supportive of the matching hypothesis. In total, 12 studies without sufficient statistical details for the meta-analysis were also examined for an indication of a crossover effect; 25% of these studies had findings indicative of a crossover interaction. Given the time and financial expenses of implementation coupled with low study quality, the benefits of matching instruction to learning styles are interpreted as too small and too infrequent to warrant widespread adoption.
... One such neuromyth involves the concept of modality-specific learning styles (LS), such as visual, auditory, and kinesthetic (sometimes referred to as VARK, which includes a reading/writing learning style). The LS neuromyth states that each individual has a learning style, based on their preference, and will learn better in that modality (Dinsmore et al., 2022). ...
... However, this neuromyth misconstrues scientific findings in a few fallacious ways. First, one predominant misinterpretation centers around the assumption that learning styles are inherent characteristics and that people will learn best when instructed in their preferred LS (Grospietsch and Lins, 2021;Dinsmore et al., 2022). The learning style neuromyth assumes a priori that intellectual styles of learning-defined by sensory input channels-exist, and that they are static aspects of learners (Pasquinelli, 2012). ...
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Despite evidence to the contrary, many people believe in learning styles (LS)–the idea that students learn best in their preferred modality, such as visual, auditory, or kinesthetic. However, the impact of this belief on instructional decisions remains unclear. Therefore, this study investigated how belief in the neuromyth impacts instructional choices and why educators choose an LS lesson plan or an alternative. We found that educators’ beliefs about LS indeed predicted their instructional choice, but that other factors influenced their decisions as well. Three themes encapsulate educators’ justifications for their lesson plan choices: beliefs about LS, practical considerations, and student learning and motivation. These findings suggest that for many educators, implementing an LS lesson provides an opportunity to integrate diverse teaching strategies that address multiple educational priorities. Although many prior studies have replicated the prevalence of the myth, this is one of the first to explore the reasons that LS is attractive to educators. Attempts to dispel the LS neuromyth could leverage the reasons educators find LS appealing to provide alternative research-backed approaches to meet their goals. Future research should examine the extent to which beliefs in the LS neuromyth are translated into instructional practices within classroom lessons and explore potential differences across grade levels.
... For example, according to Felder and Silverman's learning style model (Felder & Silverman, 1998), people with a reflective learning style prefer activities centered on theory and mathematical issues, whereas people with a sensitive learning style prefer hands-on activities. Including learning styles has been a controversial issue for some authors such as those presented in Dinsmore, Fryer and Parkinson (2022), Kirschner (2017), Riener and Willingham (2010), and Yan and Fralick (2022) who believe that learning styles are not appropriate to be taken into consideration in teacher training, lesson planning and design new content. On the other hand, the topic of learning styles continues to be a topic of current study as can be seen in Agarwal, Mishra and Kolekar (2022), Almasri (2022), Balgan, Renchin and Ojgoosh (2022), Marosan, Savic, Klasnja-Milicevic, Ivanovic and Vesin (2022), Pardamean, Suparyanto, Cenggoro, Sudigyo and Anugrahana (2022), and Troussas, Giannakas, Sgouropoulou and Voyiatzis (2023), where the authors in Agarwal et al. (2022), Marosan et al. (2022), and Pardamean et al. (2022) use Felder and Silverman's learning styles model for their research which is characterized by having a direct relationship with didactics and allows its applicability in the engineering environment. ...
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Accession Number: 2012-07127-000. Partial author list: First Author & Affiliation: Hattie, John; Melbourne Education Research Institute, University of Melbourne, Melbourne, Australia. Release Date: 20120611. Publication Type: Book (0200). Format Covered: Print. ISBN: 978-0-415-69014-0, Hardcover; 978-0-415-69015-7, Paperback; 978-0-203-18152-2, Electronic. Language: English. Major Descriptor: Academic Achievement; Learning; School Based Intervention; Teachers; Teaching Methods. Minor Descriptor: Classroom Management; Meta Analysis; Preservice Teachers; Student Teachers. Classification: Curriculum & Programs & Teaching Methods (3530). Population: Human (10). Age Group: Childhood (birth-12 yrs) (100); Adolescence (13-17 yrs) (200); Adulthood (18 yrs & older) (300). Intended Audience: Psychology: Professional & Research (PS). References Available: Y. Page Count: 269.
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The aim of the present study was to investigate how situational interest develops over time and how it is related to academic achievement in an active-learning classroom. Five measures of situational interest were administered at critical points in time to 69 polytechnic students during a one-day, problem-based learning session. Results revealed that situational interest significantly increased after the problem stimulus was presented. Subsequently, situational interest gradually decreased but at the end of the day increased again. Testing a path model relating the situational interest measures showed strong (directional) interrelations. Moreover, situational interest was highly predictive for observed achievement-related classroom behaviors. The latter, in turn, proved to be a significant predictor of academic achievement. Aggregating situational interest over the day led to less accurate predictions of achievement-related classroom behaviors and academic achievement. Implications of these findings for situational interest research are discussed.
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Our purpose in this study was to explore changes that occurred in college students’ knowledge, interests, and strategy use as a consequence of the formal instruction they received in a specific domain. This exploration is reported in three parts. Part I is a brief overview of the Model of Domain Learning—the framework upon which we based our predictions of student change. In Part II, specific changes in knowledge, interest, and strategy use of 329 undergraduate students enrolled in an introductory educational psychology course are tested and compared to predicted changes. Finally, in Part III, measures are positioned within a structural equation model allowing for a more systemic picture of the change process. Among the significant transformations we identified were increases in students’ domain knowledge and in their interests in educational psychology. Also, students’ use of text-based strategies (e.g., rereading) decreased while use of deeper-processing strategies (e.g., building a mental representation) increased from pretest to posttest. Formal instruction also affected the relationships between and among variables. Based on these findings, we forward implications for research design and methodology, as well as for instructional practice.
  • Dumas D.
Using think alouds to improve reading comprehension
  • R Farr
  • J Conner
Farr, R., & Conner, J. (2005). Using think alouds to improve reading comprehension. Retrieved from https://www.ldonline.org/using-think-alouds-improve-reading-comprehension
The teacher shortage is real, large and growing, and worse than we thought
  • Weiss Garcia
Garcia and Weiss (2019). The teacher shortage is real, large and growing, and worse than we thought. Retrived from https://www.epi.org/publication/the-teacher-shortage-is-reallarge-and-growing-and-worse-than-we-thought-the-first-report-in-the-perfect-storm-inthe-teacher-labor-market-series/