Assisted discovery-based learning for literature studies

ABSTRACT

This article evaluates the effect of discovery-based learning (DBL) in an undergraduate course in literature. The DBL method asked students in an introductory course on the Bible to discover facts about authorship and genres of various books through guided reading, followed by expository comments. The control method, in contrast, directly presented students with the expository comments. We show that students retained the target facts better in the short term with the DBL method than with the control method. Statistical analysis suggests that DBL plays a more decisive role in determining this outcome than the student’s general academic competence or background. The gain with DBL is more significant for students who successfully discovered the target facts during treatment. According to a survey, twice as many students preferred DBL than the expository approach.

KEYWORDS:

• Discovery-based learning
• inquiry-based learning
• text analysis
• religion
• e-learning

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1. We used the NET version (http://netbible.org).

2. To avoid ethics issues, all treatment items were presented to both Group 1 and Group 2 after the post-test.

3. We use this notation to refer to all books between the Letter to the Romans and the Letter to Philemon, inclusive.

4. 88.24% vs. 74.36%; the difference is not statistically significant, at p = 0.14.

5. 97.06% vs. 97.44%.

6. 72.73% vs. 74.36% for T1, and 90.91% vs. 97.44% for T4, respectively.

7. 100% vs. 97.44%, the difference is not statistically significant, at p = 0.45.

8. 95.65% vs. 74.36%, the difference is statistically significant at p=0.03

9. 100% vs. 91.18%, approaching statistical significance at p = 0.06.

Additional information

Notes on contributors

John S. Y. Lee

Dr. John S. Y. Lee is Associate Professor at the Department of Linguistics and Translation at City University of Hong Kong. He obtained his PhD in Electrical Engineering and Computer Science at the Massachusetts Institute of Technology.

Chak Yan Yeung

Dr. Chak Yan Yeung is a Postdoctoral Fellow at the Department of Linguistics and Translation at City University of Hong Kong. She earned her PhD in Linguistics at City University of Hong Kong.