933
Views
15
CrossRef citations to date
0
Altmetric
Research Article

Helping students to improve their academic performance: A pilot study of a workbook with self-monitoring exercises

, &
Pages 751-753 | Published online: 21 Aug 2012
 

Abstract

Background: There is increasing interest in developing student self-regulated learning skills, especially self-monitoring, to improve academic performance.

Aims: A pilot study to investigate the impact of self-monitoring exercises on calibration accuracy and academic performance in undergraduate medical students on a Biomedical Science (BMS) module.

Method: A randomised trial of 51 second-year students comparing a structured workbook with and without self-monitoring exercises.

Results: Participants significantly improved calibration accuracy after completing the intervention, as well as increased self-efficacy and greater satisfaction with performance. The intervention group significantly improved their BMS exam score compared with the control group.

Conclusion: A relatively simple intervention seems to have the potential to improve self-monitoring skills and academic performance. Further research is recommended to identify if the development of self-monitoring skills by a similar intervention leads to long-term improvement in academic performance, if low-performing students can significantly benefit from a similar intervention and if there is transfer of improved self-monitoring skills from one context to another.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 65.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 771.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.