Evidence map›Paper›PMID 31651301›Full record

ArticleBMC medical education2019

Teaching a difficult topic using a problem-based concept resembling a computer game: development and evaluation of an e-learning application for medical molecular genetics.

Kamila Prochazkova, Petr Novotny, Miroslava Hancarova, Darina Prchalova, Zdenek Sedlacek

Abstract readEvaluation Study
In one paragraph

Article in BMC medical education, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Data Analysis of Educational Evaluation Using K-Means Clustering Method.Computational intelligence and neuroscience · 2022
    Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Kamila ProchazkovaDepartment of Biology and Medical Genetics, Charles University Second Faculty of Medicine and University Hospital Motol, V Uvalu 84, 150 06, Prague, Czech Republic.
Petr NovotnyDepartment of Teaching and Didactics of Biology, Charles University Faculty of Science, Prague, Czech Republic.
Miroslava HancarovaDepartment of Biology and Medical Genetics, Charles University Second Faculty of Medicine and University Hospital Motol, V Uvalu 84, 150 06, Prague, Czech Republic.
Darina PrchalovaDepartment of Biology and Medical Genetics, Charles University Second Faculty of Medicine and University Hospital Motol, V Uvalu 84, 150 06, Prague, Czech Republic.
Zdenek SedlacekDepartment of Biology and Medical Genetics, Charles University Second Faculty of Medicine and University Hospital Motol, V Uvalu 84, 150 06, Prague, Czech Republic. zdenek.sedlacek@lfmotol.cuni.cz.ORCID http://orcid.org/0000-0001-6575-9163

Funding

Ministerstvo Zdravotnictví Ceské Republiky 17-29423A
6 · The paper itself

Abstract

backgroundGenetic testing rapidly penetrates into all medical specialties and medical students must acquire skills in this area. However, many of them consider it difficult. Furthermore, many find these topics less appealing and not connected to their future specialization in different fields of clinical medicine. Student-centred strategies such as problem-based learning, gamification and the use of real data can increase the appeal of a difficult topic such as genetic testing, a field at the crossroads of genetics, molecular biology and bioinformatics.

methodsWe designed an electronic teaching application which students registered in the undergraduate Medical Biology course can access online. A study was carried out to assess the influence of implementation of the new method. We performed pretest/posttest evaluation and analyzed the results using the sign test with median values. We also collected students' personal comments.

resultsThe newly developed interactive application simulates the process of molecular genetic diagnostics of a hereditary disorder in a family. Thirteen tasks guide students through clinical and laboratory steps needed to reach the final diagnosis. Genetics and genomics are fields strongly dependent on electronic databases and computer-based data analysis tools. The tasks employ publicly available internet bioinformatic resources used routinely in medical genetics departments worldwide. Authenticity is assured by the use of modified and de-identified clinical and laboratory data from real families analyzed in our previous research projects. Each task contains links to databases and data processing tools needed to solve the task, and an answer box. If the entered answer is correct, the system allows the user to proceed to the next task. The solving of consecutive tasks arranged into a single narrative resembles a computer game, making the concept appealing. There was a statistically significant improvement of knowledge and skills after the practical class, and most comments on the application were positive. A demo version is available at https://medbio.lf2.cuni.cz/demo_m/ . Full version is available on request from the authors.

conclusionsOur concept proved to be appealing to the students and effective in teaching medical molecular genetics. It can be modified for training in the use of electronic information resources in other medical specialties.

Indexed as

Computer-Assisted InstructionGenetic TestingComputational BiologyEducation, Medical, UndergraduateGenetic Diseases, InbornGenetics, MedicalHumansMolecular MedicineProblem-Based LearningTeachingUser-Computer InterfaceVideo GamesBioinformaticsE-learningGamificationGenomicsInteractive teaching applicationMedical databasesMedical geneticsProblem-based learning

Identifiers

PMID31651301
PMCPMC6813102

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.