The Revised Inventory of Learning Processes: A Multifaceted Perspective on Individual Differences in Learning

Geisler‐Brenstein, Elke; Schmeck, Ronald R.

doi:10.1007/978-94-011-0657-3_11

Cited by 13 publications

(11 citation statements)

References 35 publications

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“…This confirms the conclusions of Schmeck et al (1991 ) and Geisler-Brenstein and Schmeck (1996). Semantic was negatively predicted by Vulnerability, while Critical was positively predicted by Vulnerability (as well as by the other neuroticism scales Impulsivity and Hostility).…”

Section: Hierarchical Multiple Regression Analysessupporting

confidence: 87%

“…Notably, Geisler-Brenstein and Schmeck (1996) reached similar conclusions using different subjects and different measures of personality. Methodical Learning of a student with low academic self-esteem was predicted by high scores on the NEO-PI Extraversion subscale Warmth and the Openness subscale Actions (a lack of inhibition).…”

Section: Hierarchical Multiple Regression Analysesmentioning

confidence: 63%

“…Geisler-Brenstein and Schmeck (1996) report that students high on these scales are also high on Torrance and Rockenstein's (1988) "left-brained" thinking. It thus appears that the defining characteristic of students who habitually use Deep or Elaborative Learning is intellectual curiosity and aesthetic sensitivity.…”

Section: Exploratory Factor Analysismentioning

confidence: 99%

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An individual difference perspective on student diversity

1996

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The purpose of this study was to explore the relationships among various aspects of learning styles/strategies and personality dimensions to arrive at a "thicker" description of individual differences in functioning in general and in the school context in particular. An exploratory factor analysis of the subscales of the Inventory of Learning Processes-Revised and the NEO-Personality Inventory provided evidence for convergent and discriminant validity of six higher-order common factors. Hierarchical regression analyses were performed to differentially predict ILP-R subscales from NEO-PI subscales. The analyses were conducted separately for students identified as having high versus low academic self-esteem. The results support previous findings that self-concept variables strongly moderate relationships among personality and learning style dimensions. We discuss how the cross-fertilization between personality and learning theory and research enables us to better define what individual differences in learning consist of, how they originate, how they are manifested, what furthers or hinders their expression, and finally, to what extent they are amenable to change (maturation, development, training). Implications for school achievement, cognitive development and the productive use of individual differences in educational practice are discussed with regard to different types of learners.

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Section: Hierarchical Multiple Regression Analysessupporting

confidence: 87%

Section: Hierarchical Multiple Regression Analysesmentioning

confidence: 63%

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An individual difference perspective on student diversity

1996

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“…Four main domains were established through factor analysis-academic self-concept (in various forms), reflective processing (both deep and elaborative), "agentic" or conforming serial-reiterative processing, and methodical study. Since then, the scales have been revised again to produce the set of scales shown in Table I (Geisler-Brenstein and Schmeck, 1996), where the elements of motivation and self-efficacy have been disaggregated further, and additional social and emotional aspects have been included. It proved difficult to establish convincing parallels with other inventories for some of the scales within the most recent ILP-R on the basis of the evidence currently available; one scale (conventional attitudes) was omitted from Table I through a lack of equivalence to other inventory scales.…”

Section: Nonacademic Orientationmentioning

confidence: 99%

The Conceptual Bases of Study Strategy Inventories

Entwistle¹,

McCune²

2004

Educational Psychology Review

467

384

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This article describes the historical origins and development of a series of well-known study strategy inventories and seeks to identify their conceptual bases. The theories and evidence influencing the development of 6 contrasting instruments are considered before examining empirical evidence of similarities and differences between the measurement instruments. This analysis is tackled in three stages, looking first at inventories developed in the 1970s and 1980s that focused mainly on motivation, study methods, and learning processes. The more recent work that brought in mental models, metacognition, and self-regulation is then introduced, leading to a concluding section that discusses the conceptual bases of the whole set of inventories. The trends found in this research area are described and used to explore the current confusion of overlapping terms describing apparently similar aspects of learning and studying in higher education.KEY WORDS: approaches to studying; study strategy inventory; student learning; higher education; university.There has recently been an upsurge in interest in describing and measuring the study strategies of students in higher education. This development can be attributed, in part, to the increasing requirements on universities to justify public funding by demonstrating effectiveness and efficiency in their teaching. Moreover, convincing empirical evidence is increasingly being sought to inform policy decisions, some of which relate to the training

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“…Numerous inventories measuring cognitive, affective, and connotative aspects of learning have been developed (Garcia and Pintrich, 1996;Geisler-Brenstein and Schmeck, 1996). Likewise, numerous studies have noted what types of test different students seem to prefer (for example, Zeidner, 1987) and which tests seem biased toward particular types of students (Bolger and Kellaghan, 1990;Gamer and Engelhard, 1999).…”

mentioning

confidence: 98%

Gendered perceptions of learning and fairness when choice between exam types is offered

Mauldin

2009

Active Learning in Higher Education

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Learning processes and strategies for assessing students in higher education have been studied from a variety of different angles. Numerous inventories measuring cognitive, affective, and connotative aspects of learning have been developed (Garcia and Pintrich, 1996;Geisler-Brenstein and Schmeck, 1996). Likewise, numerous studies have noted what types of test different students seem to prefer (for example, Zeidner, 1987) and which tests seem biased toward particular types of students (Bolger and Kellaghan, 1990;Gamer and Engelhard, 1999). Still other studies have

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The Revised Inventory of Learning Processes: A Multifaceted Perspective on Individual Differences in Learning

Cited by 13 publications

References 35 publications

An individual difference perspective on student diversity

An individual difference perspective on student diversity

The Conceptual Bases of Study Strategy Inventories

Gendered perceptions of learning and fairness when choice between exam types is offered

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