Learning Preference Inventory Research Articles

Education Research: Evaluating Medical Student Learning Preference and Its Relationship to Clerkship Satisfaction.

The Accreditation Council for Graduate Medical Education and the Association of American Medical Colleges' commitment to competency-based medical education (CBME) has shifted the medical education landscape. Education methods conducive to CBME are learner-centered and give educators the opportunity to develop a more personalized approach to curricular development and delivery. By understanding learning preferences, educators are better positioned to respond to the changing needs of students. The Learning Preference Inventory (LPI) is a validated tool that assesses preferences across 3 domains: (1) content delivery (concrete vs abstract), (2) instruction (teacher-centered vs student-centered), and (3) learning structure (individual vs interpersonal). Using the LPI, our objective was to describe the learning preferences of medical students in the Neurology clerkship and to evaluate how preferences correlate with satisfaction with curricular elements. A cohort of second-year through fourth-year medical students rotating through the required Neurology clerkship at a single institution was identified. All students completed the LPI and a survey to assess satisfaction with curricular elements, including an in-person localization session, virtual simulation, and a summative case study. Five hundred thirty medical students were included. Preference for concrete content delivery was much more common than abstract (83% vs 17%); otherwise students were evenly divided in their preferences for teacher-centered vs learner-centered instruction and interpersonal vs individual learning structure. There was a significant difference in LPI responses across medical school years: More third-year and fourth-year students preferred individual learning structure compared with second-year students (p = 0.040). Learning preferences also correlated with course satisfaction survey responses. Student satisfaction with the course activities was overall positive, with 69% of students agreeing that the course enhanced their learning. Abstract learners were significantly more likely to report that the virtual simulation enhanced their learning than concrete learners (p = 0.018). Neurology clerkship students demonstrated clear learning preferences that were associated with satisfaction with specific curricular content. There were significant differences in learning preferences across medical school years, suggesting that learning preferences may shift throughout training and may be influenced by clinical exposure. In an educational environment that cultivates the success of all learners, the LPI provides important data to inform curricular development and achieve personalized medical education.

Evaluating Medical Student Learning Preference and its Relationship to Clerkship Satisfaction (S10.004)

Evaluating Medical Student Learning Preference and its Relationship to Clerkship Satisfaction (S10.004)

Validation of learning style measures: implications for medical education practice

It is unclear which learners would most benefit from the more individualised, student-structured, interactive approaches characteristic of problem-based and computer-assisted learning. The validity of learning style measures is uncertain, and there is no unifying learning style construct identified to predict such learners. This study was conducted to validate learning style constructs and to identify the learners most likely to benefit from problem-based and computer-assisted curricula. Using a cross-sectional design, 3 established learning style inventories were administered to 97 post-Year 2 medical students. Cognitive personality was measured by the Group Embedded Figures Test, information processing by the Learning Styles Inventory, and instructional preference by the Learning Preference Inventory. The 11 subscales from the 3 inventories were factor-analysed to identify common learning constructs and to verify construct validity. Concurrent validity was determined by intercorrelations of the 11 subscales. A total of 94 pre-clinical medical students completed all 3 inventories. Five meaningful learning style constructs were derived from the 11 subscales: student- versus teacher-structured learning; concrete versus abstract learning; passive versus active learning; individual versus group learning, and field-dependence versus field-independence. The concurrent validity of 10 of 11 subscales was supported by correlation analysis. Medical students most likely to thrive in a problem-based or computer-assisted learning environment would be expected to score highly on abstract, active and individual learning constructs and would be more field-independent. Learning style measures were validated in a medical student population and learning constructs were established for identifying learners who would most likely benefit from a problem-based or computer-assisted curriculum.

The Effect Of Learning Preference On Coefficient Of Variation In Maximal Muscle Performance

Human movement behaviors have been distinguished by motor learning theorists based on spatiotemporal and kinesthetic relationships. Newell's conceptual framework of motor learning calls for the sequential assembly of information processed by the brain and manifested by the acquisition of the desired coordinated movement pattern, or “skill.” Visual, auditory, and kinesthetic modalities have been identified as preferences by which adults learn. Maximal force production (MFP) is considered a psychomotor skill in view of the fact that it involves, “assigning a maximal force to the muscles in a coordinated manner (Kelso, 1982).” Accordingly, since MFP is a skill, learning must occur in order for the skill to be attained. Isokinetic dynamometry is a widely used and accepted method of quantifying dynamic MFP. While isokinetic testing protocols address each of these learning modalities, reproducibility of torque curves as measured by coefficient of variation (COV) suggests that subsequent training sessions are necessary for the learning affect to occur. However, it has not been investigated if disparate learning preferences affect variability in acquiring the skill of reproducing MFP. PURPOSE Therefore, the purpose of this study was to determine if there is a relationship between learning preference and COV in isokinetic knee extension/flexion exercise. METHODS Thirty-two novice subjects (6 males, 26 females, age 38.0 ± 13.1 yrs, ht 172.8 ± 42.7 cm, wt 64.9 ± 18.1 kg) completed the Rezler and Rezmovic Learning Preference Inventory to determine learning preference levels. Subjects were introduced to isokinetic exercise through verbal description and demonstration of the movement to accommodate auditory and visual learning. They also performed gradient warm-up repetitions to facilitate kinesthetic learning. Subjects were instructed to perform 5 maximal reciprocal repetitions of dominant knee extension/flexion at 180 d/s. RESULTS Statistical analysis revealed a significant (p<0.05) correlation between visual learning score and COV (r=.38). CONCLUSIONS Within the limitations of this study, these results suggest that there may be an inverse relationship between desirable visual learning preference and COV. Therefore, practitioners should rely on multi-modal strategies when instructing novice subjects on an isokinetic dynamometer.

The Effect Of Learning Preference On Coefficient Of Variation In Maximal Muscle Performance

Human movement behaviors have been distinguished by motor learning theorists based on spatiotemporal and kinesthetic relationships. Newell's conceptual framework of motor learning calls for the sequential assembly of information processed by the brain and manifested by the acquisition of the desired coordinated movement pattern, or “skill.” Visual, auditory, and kinesthetic modalities have been identified as preferences by which adults learn. Maximal force production (MFP) is considered a psychomotor skill in view of the fact that it involves, “assigning a maximal force to the muscles in a coordinated manner (Kelso, 1982).” Accordingly, since MFP is a skill, learning must occur in order for the skill to be attained. Isokinetic dynamometry is a widely used and accepted method of quantifying dynamic MFP. While isokinetic testing protocols address each of these learning modalities, reproducibility of torque curves as measured by coefficient of variation (COV) suggests that subsequent training sessions are necessary for the learning affect to occur. However, it has not been investigated if disparate learning preferences affect variability in acquiring the skill of reproducing MFP. PURPOSE Therefore, the purpose of this study was to determine if there is a relationship between learning preference and COV in isokinetic knee extension/flexion exercise. METHODS Thirty-two novice subjects (6 males, 26 females, age 38.0 ± 13.1 yrs, ht 172.8 ± 42.7 cm, wt 64.9 ± 18.1 kg) completed the Rezler and Rezmovic Learning Preference Inventory to determine learning preference levels. Subjects were introduced to isokinetic exercise through verbal description and demonstration of the movement to accommodate auditory and visual learning. They also performed gradient warm-up repetitions to facilitate kinesthetic learning. Subjects were instructed to perform 5 maximal reciprocal repetitions of dominant knee extension/flexion at 180 d/s. RESULTS Statistical analysis revealed a significant (p<0.05) correlation between visual learning score and COV (r=.38). CONCLUSIONS Within the limitations of this study, these results suggest that there may be an inverse relationship between desirable visual learning preference and COV. Therefore, practitioners should rely on multi-modal strategies when instructing novice subjects on an isokinetic dynamometer.

Does a Problem-solving Based Curriculum Develop Life-long Learning Skills in Undergraduate Students?

Background and purpose In preparing undergraduates for professions that require a commitment to continuing professional development, Higher Education has an obligation to ensure that its graduates have the ability, confidence and desire to continue as educationally self-directed learners. It is suggested that undergraduate curricula can be used to facilitate self-directed learning development. This study compared the learning profile development over time of two full-time BSc(honours) Physiotherapy cohorts (C94 and C98) who experienced different curricular presentations of the same syllabus. Curricular changes intended to facilitate self-directed learning development were introduced before the second cohort. Methods Both cohorts completed the Guglielmino (1977) Self-directed Learning Readiness Scale and the Rezler and French (1975) Learning Preference Inventory on admission, at four selected points during the three-year courses, and seven months after graduation. A repeated measures analysis of variance was used to test for cohort change with change over time tested using a first order polynomial contrast. Results Completed sample sizes were C94 = 31, C98 = 36. On admission both cohorts preferred a fact-based learning environment that was teacher-structured. Both curricula influenced students' learning profile development over time. C98 responded differently (p < 0.05) from C94. The former were better able to learn in student-structured, interpersonal and individual learning environments. Seven months after graduation, the learning environment flexibility of the C98 cohort had reduced. Conclusions C98 responded positively to the curricular changes introduced as an attempt to reduce dependence on the teacher of C94. However, these changes were short-term and did not extend into early postgraduate life, bringing into question the ability of the professional environment to reinforce and encourage fledgling postgraduate learning development.

Learning preferences, computer attitudes, and student evaluation of computerised instruction

To explore the relationship between learning preferences, attitudes towards computers, and student evaluation of a computer-assisted instructional (CAI) program. A third year required clerkship in surgery at the University of Nebraska Medical Center. A mixed-methods design combining attitudinal measures and qualitative interviews was employed to assess student reactions to a CAI program on angiography completed during a required surgical clerkship. Between January 1998 and July 1999, 151 students completed the program. Prior to participating, students completed the Rezler Learning Preference Inventory (LPI) and a computer attitudes survey (CAS). The LPI characterizes learning preferences as being abstract or concrete, individual or interpersonal, and student-structured or teacher-structured. The CAS measures attitudes towards computers and their role in education. After using the CAI program, students evaluated the module by completing an 18 item questionnaire. Based on LPI and CAS scores, 31 students were invited to participate in an in-depth qualitative interview on their experiences and perceptions of the program. There was no relationship between learning preferences, computer attitudes, and evaluation of the CAI program. Students were very positive about the program's content, clarity, organization, and ease of use. They also rated it as efficient and effective. However, many still indicated a preference for lecture and text-based learning. Qualitative interviews suggest students worry computers will supplant student--teacher contact. Learning preferences and prior attitudes toward computers did not bias student reactions to the CAI program assessed in this study. However, students expressed concerns that CAI would interfere with the traditional student--teacher encounter and relationship.

Learning preferences, computer attitudes, and test performance with computer-aided instruction

Background: Learning preference refers to how individuals choose to approach learning situations. Computer-aided instruction (CAI) permits the adaptation of educational content to individual student learning strategies. Methods: To determine if learning preference and computer attitude influence the acquisition of knowledge using CAI materials, a prototype CAI program was developed that incorporated differing learning exercises. Students (n = 180) completed Rezler’s Learning Preference Inventory (LPI) and a computer attitude survey (CAS). The LPI uses three sets of paired scales to characterize learning preference and choice of learning situation. The CAS assesses student attitudes toward computers in general (CAS-G), as well as the educational use of computers (CAS-E). After finishing the program students completed a program attitude survey (CAS-P). Immediate comprehension was assessed by pretests and posttests incorporated into the program. Retention was assessed by a repeat of the posttest 4 to 6 weeks after initial program review. Results: Scores (mean ± SEM) on the pretest, posttest, and late posttest were 38.1% ± 1.35%, 70.9% ± 1.24%, and 62.5% ± 1.44%, respectively. There was no correlation between students’ learning preferences or computer attitude and test performance. Conclusions: The data indicate that CAI provides a means of delivering educational content that results in an increase in knowledge that is not correlated with computer attitudes or learning preferences.

How Do Our New Graduates Prefer To Learn?

Background: Learning preference refers to one's choice of specific learning situations or environments over the other. It is one of the factors needed to be considered in planning curriculum and in designing instructional units. Objectives: The primary objectives of this study were to characterize the learning preference of recent medical graduates of the National University of Singapore (NUS) and to identify any possible gender differences.This study is likely to be first of its kind in this learner population. Instrument: Rezler's Learning Preference Inventory. Methods: Rezler's Learning Preference Inventory was administered among twenty-eight 1997 graduates (male 16, female 12) of NUS. The independent variable was the gender and the dependent variables were the scores in each of the learning categories: abstract, concrete, teacher-structured, student-structured, interpersonal, and independent. Analysis: Frequency distribution of the learning preferences was counted manually. Independent samples t-test was used to compare two groups of dependent variables. Results: Ninety-two percent female and sixty-nine percent male respondents preferred concrete learning. Only one male respondent and none of the female respondents preferred abstract learning. Among all the respondents, differences between concrete and abstract categories reached statistical, as well as meaningful, significance (p < 0.0001 and mean score difference of 19.9). Differences between student-structured and teacher-structured, and between interpersonal and independent categories did not reach statistical significance (p value of 0.5l and 0.78 respectively). Female respondents generally showed a trend towards greater preference for concrete and teacher-structured learning than their male counterparts. Conclusion: The learning preferences of recent graduates of the NUS is characterized by high inclination towards concrete learning.The results can be utilized in designing instructional methods for this group of learners.

Learning preference and personality type: their association in paediatric residents.

The objective of this study was to determine if there is a relationship between the learning preferences and personality types of residents in paediatrics. As part of a study to teach residents in paediatrics how to teach, the authors administered the Learning Preference Inventory (LPI) and Fundamental Interpersonal Relationship Orientation (FIRO-B) instruments to 55 residents in paediatrics at all three levels of training. The instruments provided data that were used to provide feedback to residents on their learning preferences and interaction styles, as well as how these factors might affect teaching and learning in the clinical setting. The Pearson correlation coefficient was used to determine relationships between the LPI and the FIRO-B. Fifty-two of the 55 residents (95%) completed the instruments. The results revealed that residents' learning preferences were significantly related to their personality types. For example, residents with high inclusion and affection scores on the FIRO-B preferred learning with others, which was significantly related to their high interpersonal scores on the LPI. Residents with low inclusion and affection scores were more likely to prefer independent learning (high individual and student-structured scores on the LPI) and abstract learning at statistically significant levels. The scores obtained by residents in paediatrics on the LPI were strongly correlated with those obtained on the FIRO-B. These data may have important implications for the way in which staff recruit, counsel and teach residents. The fact that the LPI is easy to administer and does not purport to measure personality styles makes it an acceptable educational tool that can be used in many areas of training.

Correlation of conference attendance, intraining exam scores, and learning preference inventory in emergency medicine residents : Ferraro, CM, University of Illinois Affiliated Residency in Emergency Medicine, Mercy Hospital and Medical Center, Chicago, Illinois, USA

Correlation of conference attendance, intraining exam scores, and learning preference inventory in emergency medicine residents : Ferraro, CM, University of Illinois Affiliated Residency in Emergency Medicine, Mercy Hospital and Medical Center, Chicago, Illinois, USA

A Comparative Study of Learning Characteristics of RN and Generic Students

The constructs of locus of control, self-directed learning readiness, and learning style preference are related components of an individual's learning characteristics. If group differences between registered nurse and generic students on these constructs could be documented, then the educational process could be directed toward facilitating educational goal attainment for these two distinct groups of students. Three instruments were used for this study: the Adult Nowicki-Strickland Internal-External Scale (ANS-IE), Guglielmino's Self-Directed Learning Readiness Scale (SDLRS), and Rezler's Learning Preference Inventory (LPI). The sample consisted of 175 generic and 170 RN students enrolled in two BSN programs. No significant group differences were found for the three constructs except for the interpersonal mode of learning, a subscale of the LPI. Although no group differences were found, the data showed an ethnic and age effect involving all subjects. Although there are no wide differences in learning characteristics between generic and RN students, the individual variations support the use of teaching strategies that incorporate independent study and self-paced methodologies.

Beyond career choice: the role of learning style analysis in residency training.

A recent article in this journal took an important step toward rethinking the utility of behavioural instruments designated as learning style tests (Jewett et al. 1987). The authors of that paper made much of a distinction between the terms 'learning style' and 'learning preference'. However, the results of their study do not seem to substantiate a marked difference between the function of the Rezler Learning Preference Inventory (LPI) and Kolb's Learning Style Inventory (LSI) with which it was contrasted. The most important aspect of their paper was that it rescued the concept of learning style analysis from the arena of career choice prediction at the undergraduate level and applied these ideas to doctors who had already made their specialty selections and were actively engaged in residency training. Clinical instructors in teaching institutions have, for the most part, little or no formal background in educational principles. For these individuals, an easily comprehensible model of resident-instructor psychology can be very useful on a daily basis. This article reviews the authors' experience with the LSI and describes their utilization of Kolb's Experimental Learning Model in the areas of resident counselling and residency curriculum design. The results of two recent studies are also presented in which learning style was examined as a predictor of success in residency, and teacher-resident learning style distributions were shown to exhibit parallel relationships at four different anaesthesiology residency training programmes.

Another look at career choice and learning preferences.

The learning styles and preferences of health professionals have been studied increasingly over the past decade, yet few relationships have been found between doctors' career choices and learning styles. One of the problems of relating learning styles to specialty choice is that learning style instruments measure how an individual perceives and processes information in learning situations. This study re-examines doctors' career choices utilizing a learning preference inventory which assesses how one chooses to approach a learning situation. The study results indicate that there are significant differences in doctors' approaches to learning and interacting with others among the different career specialties using a learning preference inventory. This is in contrast to previous research with Kolb's Learning Style Inventory in which learning style was not found to be related to career choice.

Educational Experience and Changes in Learning and Value Preferences

Education attempts to instill certain values, as well as knowledge and skills, in students. Yet, examination of value changes is infrequent, and the findings of existing studies are equivocal. This article reports on a study of value and learning preference changes in occupational therapy students. Two small groups of undergraduate and graduate students completed the Rokeach Value Survey, the Learning Preference Inventory, and an educational values inventory (developed by the first two authors) at the beginning of their professional education and again while on affiliation. Four other groups completed the instruments once: undergraduate and graduate students in the first semester of the professional program, and undergraduate and graduate students in the second semester. For the students who participated in the study twice, undergraduates were more likely than graduates to rearrange their value priorities, and changes were more likely to occur with educational values than Rokeach values. However, although individuals may have changed substantially, when subjects were treated as a group changes tended to be masked. Comparisons of first semester, second semester, and affiliating undergraduates and graduates revealed few differences among groups, although again, educational values differed more than Rokeach values. Because the study seems to suggest that individuals are affected in varying ways by their education, a major implication is that a methodology for examining the impact of professional education must account for initial differences in students.

774 ANOTHER LOOK AT CAREER CHOICE AND LEARNING STYLES

Few relationships have been found between physicians' career choices and learning and personality styles. This study re-examines physicians' career choices utilizing a learning preference inventory which assesses approaches to learning. METHOD: The majority of residents in the specialties of internal medicine (62), obstetrics/gynecology (16), pediatrics (52), psychiatry (15), and surgery (24) completed the Rezler Learning Preference Inventory, and the FIRO-B Scale. The analysis method to determine differences was an ANOVA. RESULTS: Residents in all specialties except psychiatry had strong preferences for concrete, practical learning while many psychiatry residents prefer learning theoretically (p .05). Significantly more (p .05) psychiatry residents preferred teacher structured learning while residents in other specialties were more likely to prefer student-structured learning (p .05). Pediatric residents preferred learning with others (p .05) while ob/gyn residents preferred independent learning such as reading (p .05). On the FIRO-B Scale which measures typical ways individuals interact with other people, pediatric residents as compared to the other specialties were more likely to want others involved in their activities and to have warm and personal relationships instead of doing things alone or have businesslike relationships.

FACTORS INFLUENCING CAREER CHOICE AND SATISFACTION IN PEDIATRICS

The “dissatisfied pediatrician syndrome” has been manifested in an extremely high career burn-out rate among pediatricians. This study's purpose was to cite factors which lead to career satisfaction and dissatisfaction or burn-out in pediatricians. METHODOLOGY: Pediatricians (87) surveyed in Washington, D.C. and at the fall 1983 AAP meeting career assessment exhibit (125) completed a questionnaire, the FIRO-B Scale, and Rezler Learning Preference Inventory. 63% were in practice, 32% in academics, and 5% in research or other. 73% were males; 27% were females. RESULTS: Many pediatricians, unrelated to career choice or satisfaction, reported feeling stressed and tense. Dissatisfying factors were: long hours, busy workloads, inadequate remuneration, stress, and malpractice threats. Academicians found the difficulty of balancing patient care, administration, research, and teaching responsibilities and the lack of support and time for research and teaching to be dissatisfying. Practitioners reported endless telephone calls, practice management, insecurity, routine work, limited time for research and teaching and lack of contact with peers to be dissatisfying. The time spent in patient care, teaching, administration, and research were found to significantly correlate with career satisfaction. Career profiles for pediatricians in practice and academics were predictable based on study results.

Learning Preference Inventory

In this series we print evaluation instruments, questionnaires, rating scales and similar resource materials useful to teachers, evaluators and planners. You may wish to adapt such instruments for your own purposes. The feature this issue was developed by Professor A. G. Rezler, PH.D, Center for Educational Development, University of Illinois in Chicago, 808 South Wood, Chicago, Illinois 60612, USA, from whom the inventory can be obtained, together with a set of answer sheets (not shown here).