Liahona Hamblin and Dr. Jamie Jensen, Department of Biology

The purpose of this study was to test student resistance to the inquiry method of instruction in tertiary introductory biology classes. Proven to be beneficial, the “inquiry” method differs from confirmatory “cookbook” laboratory experiences in that students explore phenomena and solve problems (Prince & Felder, 2007). This research was sparked by evidence that students tend to show resistance to student-centered instruction (of which inquiry is a part) (Felder, 2011; Prince & Felder, 2007). This research began with three specific aims: to define resistance based on learning theory, to quantify that resistance, and to test our hypotheses that reasoning ability, learning style, and preconceived notions and attitudes are correlated to resistance. The intended outcome of this research was to identify a possible cause of why students resist and then to propose a causal mechanism to be manipulated in the future in order to overcome this resistance.

We defined resistance according to the following factors: ability to stay on task, appeal, perceived usefulness and suitability of the inquiry activity/lesson. Resistance was measured quantitatively by a likert scale rating each factor. A qualitative survey given once during each semester (which was later quantified by two researchers) rated similar factors plus self-reported prior knowledge, expectations, perceived ease of course content, preference for lecture vs activities etc. We also gathered data on student reasoning (via the Lawson Classroom Test of Scientific Reasoning, LCTSR), prior biological science knowledge (via the Introductory Molecular and Cellular biology Assessment, IMCA), learning styles (via the Inventory of Learning Styles, ILS), and low-level (LL) and high-level (HL) Blooms test achievement. We compared each of these to resistance factor scores by running Pearson Correlations using the SPSS statistical package. Fall assessment data was manually pulled off Blackboard one student at a time as well as hardcopy quantitative surveys tallied and averaged by hand. During winter we abolished the hard copy surveys to save time, giving students special instructions to enter answers via email, weekly quizzes, and Qualtrics. We still managed to get sufficient student participation and data regardless, but encountered many inconsistencies between semesters. Fall acted as more of a pilot study while improved methods may have produced more reliable data in Winter. Also, our proposed method to test the preconceived notions/attitude hypothesis by convincing half of the students of the effectiveness of inquiry failed due to timing issues and working with other professors. So, we relied on qualitative survey evidence for correlation.

Reasoning Ability Results

We found no significant correlation between reasoning ability and any of our resistance factors in the quantitative surveys for either semester. The only significant correlation found was between LCTSR and written survey scores for “On Task” in Fall, and a positive correlation between LCTSR and “lecture preference over activities” and “perception of class content ease” in Winter. These correlations are inconsistent between semesters and so we interpret them cautiously. We found that average LCTSR reasoning scores for both semesters were relatively high (Fall 18.66/Winter 17.79 out of 24) as is consistent with a generally gifted BYU population and thus perhaps correlating resistance scores with a more varied reasoning population would have been more telling. Expectedly, we found a positive correlation between LCTSR score and test scores. We conclude that while reasoning ability solidly correlates to ability and test success it may not influence their resistance to the method of learning according to the resistance factors we tested for. This indicates that inquiry instruction should not disadvantage any particular reasoning level because of predisposition to resistance.

Learning Style Results

Over all we found that student learning styles as indicated by ILS do not significantly correlate with quantitative resistance factor scores consistently (both semesters). Both semester groups had a good mix of learning styles, and interestingly even the most resistant on one factor (25% perceived “Usefulness” on quantitative survey) had a good mix of learning styles. There were many significant correlations between learning style and LL/HL results signifying that some style learners are better at taking tests. Significant correlations were also plentiful between learning style and qualitative survey preferences but also inconsistent across both semesters. This indicated that learning styles have no consistent influence on attitudes about inquiry and thus no group should be disadvantaged by their resistance.

Prior Knowledge/Preconceived Notions/Attitudes Results

We found that both semesters had a good mix of student from both ends of the prior-knowledge and expectations spectrums. In both semesters we found a significant correlation between quantitative self-reported “Suitability” and IMCA score. The more prior biology knowledge students had, the more juvenile they found the activity, while the less prior knowledge they had, the more appropriate they found the activities. From the written surveys we find multiple significant correlations: the higher the IMCA the less useful they found in-class activities (W), the more they preferred lecture (W), and the less challenging they found the content (F/W). In contrast, self-reported ratings for both semesters indicated that students were mostly engaged and generally believed the teacher’s methods matched their perceived learning style. In summary, prior knowledge does seem to have a direct relationship with student resistance—those with more prior knowledge tend to resist inquiry more. Student preference for lecture or learning method, however, may not deem a student “resistant” under our complete set of factors (particularly whether they were “On Task” or not).

Other unknown variables may be the cause of resistance and further study is certainly warranted. Prior biology knowledge seems to be the most influential factor in students’ perceived usefulness of inquiry: meaning that students past experience predispose them to resistance. However, we saw no trend indicating that these attitudes affect performance in the course or engagement. Thus, they do not appear to fully influence true resistance as based on all our defined factors. Further comparison of prior-knowledge/attitude to LL/HL score/class outcome and additionally, comparing true resistors who score low on all factors to LL/HL scores/class outcomes would be good to rule out the possibility that resistance harms student outcome. If resistance does not harm outcomes then we know that any correlation to resistance would not support the discontinuation of the use of inquiry. In the meantime our data supports the use of inquiry methods because it does not support the notion that the particular student groups we tested will be predisposed to resistance (whether resistance is harmful or not). I acknowledge the aid of ORCA, as well as Dr. Jensen and her team of undergraduate researchers for guidance and help. We plan to submit a paper to be published in the near future.

References

• Felder, R. M. (2011). Hang in there: dealing with student resistance to learner-centered teaching. Chem. Engr. Education, 45(2), 131-132.
• Prince, M., & Felder, R. (2007). The many faces of inductive teaching and learning. Journal of College Science Teaching, 36(5).