Literature DB >> 24449123

Learning with interactive computer graphics in the undergraduate neuroscience classroom.

John R Pani1, Julia H Chariker, Farah Naaz, William Mattingly, Joshua Roberts, Sandra E Sephton.   

Abstract

Instruction of neuroanatomy depends on graphical representation and extended self-study. As a consequence, computer-based learning environments that incorporate interactive graphics should facilitate instruction in this area. The present study evaluated such a system in the undergraduate neuroscience classroom. The system used the method of adaptive exploration, in which exploration in a high fidelity graphical environment is integrated with immediate testing and feedback in repeated cycles of learning. The results of this study were that students considered the graphical learning environment to be superior to typical classroom materials used for learning neuroanatomy. Students managed the frequency and duration of study, test, and feedback in an efficient and adaptive manner. For example, the number of tests taken before reaching a minimum test performance of 90 % correct closely approximated the values seen in more regimented experimental studies. There was a wide range of student opinion regarding the choice between a simpler and a more graphically compelling program for learning sectional anatomy. Course outcomes were predicted by individual differences in the use of the software that reflected general work habits of the students, such as the amount of time committed to testing. The results of this introduction into the classroom are highly encouraging for development of computer-based instruction in biomedical disciplines.

Entities:  

Mesh:

Year:  2014        PMID: 24449123      PMCID: PMC4107209          DOI: 10.1007/s10459-013-9483-3

Source DB:  PubMed          Journal:  Adv Health Sci Educ Theory Pract        ISSN: 1382-4996            Impact factor:   3.853


  21 in total

1.  Active and passive scene recognition across views.

Authors:  R F Wang; D J Simons
Journal:  Cognition       Date:  1999-03-01

2.  Acquiring new spatial intuitions: learning to reason about rotations.

Authors:  John R Pani; Julia H Chariker; Thomas E Dawson; Nathan Johnson
Journal:  Cogn Psychol       Date:  2005-09-13       Impact factor: 3.468

Review 3.  The research we still are not doing: an agenda for the study of computer-based learning.

Authors:  David A Cook
Journal:  Acad Med       Date:  2005-06       Impact factor: 6.893

4.  When static media promote active learning: annotated illustrations versus narrated animations in multimedia instruction.

Authors:  Richard E Mayer; Mary Hegarty; Sarah Mayer; Julie Campbell
Journal:  J Exp Psychol Appl       Date:  2005-12

5.  A natural language intelligent tutoring system for training pathologists: implementation and evaluation.

Authors:  Gilan M El Saadawi; Eugene Tseytlin; Elizabeth Legowski; Drazen Jukic; Melissa Castine; Jeffrey Fine; Robert Gormley; Rebecca S Crowley
Journal:  Adv Health Sci Educ Theory Pract       Date:  2007-10-13       Impact factor: 3.853

Review 6.  Computer animations in medical education: a critical literature review.

Authors:  Jorge G Ruiz; David A Cook; Anthony J Levinson
Journal:  Med Educ       Date:  2009-09       Impact factor: 6.251

Review 7.  Is learning anatomy facilitated by computer-aided learning? A review of the literature.

Authors:  M D B S Tam; A R Hart; S Williams; D Heylings; S Leinster
Journal:  Med Teach       Date:  2009-09       Impact factor: 3.650

Review 8.  Teaching basic science to optimize transfer.

Authors:  Geoff Norman
Journal:  Med Teach       Date:  2009-09       Impact factor: 3.650

9.  Computer-Based Learning: Graphical Integration of Whole and Sectional Neuroanatomy Improves Long-Term Retention.

Authors:  Farah Naaz; Julia H Chariker; John R Pani
Journal:  Cogn Instr       Date:  2014

10.  Computer-based learning: interleaving whole and sectional representation of neuroanatomy.

Authors:  John R Pani; Julia H Chariker; Farah Naaz
Journal:  Anat Sci Educ       Date:  2012-07-03       Impact factor: 5.958

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  2 in total

1.  Comparing computer-assisted learning activities for learning clinical neuroscience: a randomized control trial.

Authors:  Kiran Kasper Rajan; Anand S Pandit
Journal:  BMC Med Educ       Date:  2022-07-03       Impact factor: 3.263

2.  A recommended workflow methodology in the creation of an educational and training application incorporating a digital reconstruction of the cerebral ventricular system and cerebrospinal fluid circulation to aid anatomical understanding.

Authors:  Amy Manson; Matthieu Poyade; Paul Rea
Journal:  BMC Med Imaging       Date:  2015-10-19       Impact factor: 1.930

  2 in total

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