The effect of the personalization principle on multimedia learning: the role of student individual interests as a predictor

Schrader, Claudia; Reichelt, Maria; Zander, Steffi

doi:10.1007/s11423-018-9588-8

Cited by 18 publications

(16 citation statements)

References 20 publications

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“…By now, there are only a few attempts to examine possible mechanisms using mediation or moderation analyses. While there are single studies on social cues examining the effects of social cues moderated by motivational variables (e.g., Endres et al 2020 ; Schrader et al 2018 ), emotional processes (e.g., Kühl and Zander 2017 ; Liew et al, 2017 ), or cultural variables (Brom et al 2017 ), even fewer studies analyzed social processes as mediators of included social cues (Araujo 2018 ; Gunawardena and Zittle 1997 ). In particular, it should be fathomed when, how, and to what extent social cues prove to be conducive or a possible hindrance to learning.…”

Section: Discussionmentioning

confidence: 99%

The Cognitive-Affective-Social Theory of Learning in digital Environments (CASTLE)

et al. 2021

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For a long time, research on individuals learning in digital environments was primarily based on cognitive-oriented theories. This paper aims at providing evidence that social processes affect individual learning with digital materials. Based on these theories and empirical results, a social-processes-augmented theory is suggested: the Cognitive-Affective-Social Theory of Learning in digital Environments (CASTLE). This CASTLE postulates that social cues in digital materials activate social schemata in learners leading to enhanced (para-)social, motivational, emotional, and metacognitive processes. To substantiate this theory, socio-cognitive theories are used, which predict social influences on learning with digital materials. Besides, previous empirical findings are presented assuming that with a rising number of social cues in digital materials, the influence of social processes increases. Finally, consequences regarding the design of digital learning media are discussed.

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Section: Discussionmentioning

confidence: 99%

The Cognitive-Affective-Social Theory of Learning in digital Environments (CASTLE)

et al. 2021

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“…Finally, future research should take into account students' prior knowledge of and interest in the learning content. Both learner characteristics have been found to affect the interplay between a personalized language format and learning performance (see, respectively, Stiller & Jedlicka, ; Schrader et al, ). This would fit the more general belief that especially in mathematics, heterogeneity in motivational and emotional factors are relevant to consider in relation to learners' experiences with and performance on a task (Meece, Glienke, & Burg, ).…”

Section: Discussionmentioning

confidence: 99%

“…This means that, in terms of word problem solving processes, problem solvers may not invest enough effort into trying to accurately represent the problem statement, which in inconsistent word problems includes the challenge of reversing the relational keyword into the opposite arithmetic operation. Given that personalized language in word problems and learning tasks increases motivation and interest (e.g., Davis‐Dorsey et al, ; Schrader, Reichelt, & Zander, ), directly addressing the problem solver by using the pronoun “you(r)” in the word problem is expected to increase the likelihood that they construct more accurate mental representations of the problem statement hidden in an inconsistent word problem due to heightened involvement, connectedness with, and personal relevance of the word problem (Brunyé et al, ; Libby et al, ; Mayer, ). By stepping into the described problem situation, problem solvers analyze the problem more carefully, and therefore be more sensitive to linguistic cues (e.g., you) that could help them understand the described problem.…”

Section: Introductionmentioning

confidence: 99%

Can “you” make a difference? Investigating whether perspective‐taking improves performance on inconsistent mathematical word problems

Koning

Schoot

2019

Applied Cognitive Psychology

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Pronouns encouraging a second-person perspective (e.g., "you/your") affect peoples' mental representations constructed while reading and improve learning. The present study applied these insights to a domain in that such pronoun effects have yet been unexplored: mathematical word problem solving. Specifically, we encouraged a second-person perspective (using "your") in an attempt to reduce the consistency effect, that is, the finding that more errors are made on word problems containing a relational keyword inconsistent rather than consistent with the required arithmetic operation. Primary school children solved consistent and inconsistent word problems (containing the relational keywords "less than") presented in third-person (i.e., store name) or second-person ("your store") perspective. Results demonstrated the consistency effect, but the perspective manipulation did not produce significant differences between conditions, that is, a second-person perspective did not reduce the consistency effect. These findings suggest that reducing the consistency effect may require a less subtle approach than using personalized pronouns. KEYWORDS consistency effect, personalization effect, primary education, reading comprehension, word problem solving

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“…Castro et al [117] and Wong et al [118] established the relationship between cognitive overload and learning modality. Similarly, the effectiveness of multimedia based e-learning is conditional to its presentation, as observed in [119] [120] [121]. All of these ideas suggest a need of the integration of adaptable modality determination and subsequent recommendation of learning resources for the realization of personalized e-learning.…”

Section: Adaptation Of Learning Modalitymentioning

confidence: 99%

AI-Based Personalized E-Learning Systems: Issues, Challenges, and Solutions

et al. 2022

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A personalized e-learning system is effective in imparting enhanced learning to its users. As compared to a conventional e-learning system, which provides similar contents to each learner, a personalized learning system provides specific learning contents and assessments to the learners. Personalization is based on Artificial Intelligence (AI) based techniques in which appropriate contents for each learner are determined using the level of comprehension of the learner and the preferred modes of learning. This paper presents requirements and challenges for a personalized e-learning system. The paper is focused in elaborating four research questions, which are related to identifying key factors of personalized education, elaborating on state of the art research in the domain, utilizing benefits of AI in personalized education, and determining future research directions. The paper utilizes an extensive survey of current research papers in answering these questions. It provides a comprehensive review of existing solutions in offering personalized e-learning solutions. It also elaborates on different learning models and learning theories, which are significant in providing personalized education. It proposes an efficient framework, which can offer personalized elearning to each learner and identifies significant directions for future research. The paper is beneficial for academicians and researchers in understanding the requirements of such a system, comprehending its methodologies, and identifying challenges which are needed to be addressed.

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The effect of the personalization principle on multimedia learning: the role of student individual interests as a predictor

Cited by 18 publications

References 20 publications

The Cognitive-Affective-Social Theory of Learning in digital Environments (CASTLE)

The Cognitive-Affective-Social Theory of Learning in digital Environments (CASTLE)

Can “you” make a difference? Investigating whether perspective‐taking improves performance on inconsistent mathematical word problems

AI-Based Personalized E-Learning Systems: Issues, Challenges, and Solutions

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