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Assessing learning styles using a computerized learning style inventory

Billings, D.M.

Computers in Nursing 9(3): 121-125

1991

ISSN/ISBN: 0736-8593
PMID: 2059896
Document Number: 372402
Faculty in academic and service settings are searching for mechanisms for improving effectiveness and efficiency of teaching students with diverse learning styles. This article describes the Dunn, Dunn, and Price Productivity Environmental Preference Survey (PEPS), a computerized learning style inventory, that provides both individual and group summaries for learning style preference on 20 subscales. The validity and reliability of the instrument for nurses is reported. Practical suggestions are offered for using the individual and group results of the inventory. The use of the inventory has added benefits of improving computer literacy for novice users.

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Mala-Maung; Abdullah, A.; Abas, Z.W. 2011: Appreciation of learning environment and development of higher-order learning skills in a problem-based learning medical curriculum Medical Journal of Malaysia 66(5): 435-439
Wismar, D.L.; Collart, M.E. 1976: Learning styles of EMT's Emergency Medical Services 5(3): 49-50; 52, 64
Peota, C. 2010: Learning styles Minnesota Medicine 93(11): 11-13
Janing, J. 2001: Linking teaching approaches and learning styles: how can it help students? Emergency Medical Services 30(9): 77-80
Kjerland, G..; Annerstedt, C. 2021: Applying learning theories in learning how to teach physical education: a study of teacher education students collaborative learning processes in a project Sport, Education and Society: 1-14
Chase, T.M. 2001: Learning styles and teaching strategies: enhancing the patient education experience Sci Nursing: a Publication of the American Association of Spinal Cord Injury Nurses 18(3): 138-141
Sahoo, S. 2016: Finding self-directed learning readiness and fostering self-directed learning through weekly assessment of self-directed learning topics during undergraduate clinical training in ophthalmology International Journal of Applied and Basic Medical Research 6(3): 166-169
Sahoo, S. 2016: Finding self-directed learning readiness and fostering self-directed learning through weekly assessment of self-directed learning topics during undergraduate clinical training in ophthalmology International Journal of Applied and Basic Medical Research 6(3): 166-169
Llorens, L.A.; Adams, S.P. 1978: Learning style preferences of occupational therapy students American Journal of Occupational Therapy: Official Publication of the American Occupational Therapy Association 32(3): 161-164
Christensen, M.G.; Lee, C.A.; Bugg, P.W. 1979: Professional development of nurse practitioners as a function of need motivation, learning style, and locus of control Nursing Research 28(1): 51-56
Arguello Casteleiro, M.; Maseda Fernandez, D.; Demetriou, G.; Read, W.; Fernandez Prieto, M.J.; Des Diz, J.; Nenadic, G.; Keane, J.; Stevens, R. 2017: A Case Study on Sepsis Using PubMed and Deep Learning for Ontology Learning Studies in Health Technology and Informatics 235: 516-520
Brigley, S.; Hosein, I.; Myemba, I. 2009: Placing learning needs in context: distance learning for clinical officers in Tanzania Medical Teacher 31(4): E169-E176
Hutton, C.W.; Davidson, S.H. 1979: Self-instructional learning packages as a teaching/learning tool in dietetic education Journal of the American Dietetic Association 75(6): 678-681
Su, Y.-S.; Lin, Y.-D.; Liu, T.-Q. 2022: Applying machine learning technologies to explore students' learning features and performance prediction Frontiers in Neuroscience 16: 1018005
Murayama, Y. 1980: A trial in problem-solving learning process by groups--for establishing active learning attitudes Kango Tenbo. Japanese Journal of Nursing Science 5(9): 854-860
Shiota, M.; Koeda, T.; Takeshita, K. 1997: Clinical studies of learning disability. Part III: Prevalence of children with suspected learning disabilities No to Hattatsu 29(2): 145-148
Friedman, C.; Rubin, J.; Brown, J.; Buntin, M.; Corn, M.; Etheredge, L.; Gunter, C.; Musen, M.; Platt, R.; Stead, W.; Sullivan, K.; Van Houweling, D. 2015: Toward a science of learning systems: a research agenda for the high-functioning Learning Health System Journal of the American Medical Informatics Association: Jamia 22(1): 43-50
Moss, V.A. 1994: Assessing learning abilities, readiness for education Seminars in Perioperative Nursing 3(3): 113-120
Khumrin, P.; Ryan, A.; Judd, T.; Verspoor, K. 2017: Diagnostic Machine Learning Models for Acute Abdominal Pain: Towards an e-Learning Tool for Medical Students Studies in Health Technology and Informatics 245: 447-451
Marambe, K.N.; Athuraliya, T.Nimmi.C.; Vermunt, J.D.; Boshuizen, H.Pa. 2007: A comparison of learning strategies, orientations and conceptions of learning of first-year medical students in a traditional and an innovative curriculum Annals of the Academy of Medicine Singapore 36(9): 751-755