Modified Approaches And Study Skills Inventory For Students

(Post last updated June 24, 2022)

Review panel summary

The Modified Approaches and Study Skills Inventory for Students (M-ASSIST) is an assessment targeting students’ deep and surface study approaches using a five-point Likert response scale. The M-ASSIST consists of 12 items (6 items each for deep and surface approaches) and was developed based on the original ASSIST instrument with slight modifications to reflect American English [1]. The original authors claimed the ASSIST was based on the conceptual framework of deep and surface approaches to learning, but did not provide explicit content validity evidence to support this [1]. Internal structure validity evidence was provided by conducting a confirmatory factor analysis of a two-factor model for deep and surface study approaches, where a good fit was demonstrated [1]. Measurement invariance testing between students grouped by grades revealed an acceptable fit, therefore, authors used the M-ASSIST to compare deep and surface learning between these groups. This testing provided evidence for true differences across groups rather than differences in instrument function [1]. Evidence for relations to other variables was presented in the comparison of deep and surface scores to students’ study skills/lecture habits [2].

Recommendations for use

The M-ASSIST was developed to measure students’ deep and surface study approaches and is not intended to be used as a total score. Rather, each subscale provides information about respective study skills based on the presented internal structure validity evidence [1]. Based on the measurement invariance evidence, M-ASSIST has shown the ability to measure deep and surface learning approaches across students grouped by course grade [1]. While there is substantial evidence for the internal structure, additional evidence supporting test content and response process would provide further support for the data derived from the M-ASSIST.

Details from panel review

Authors conducted an ANOVA and structured means models (SMM) to compare student study approaches across achievement groups based on course grades. The two methods for comparing groups were presented, where SMM detected small group differences of the latent variable means resulting in a better measurement of the constructs of interest (deep and surface study approaches) [1]. The deep subscale score was less sensitive than the surface score across student groups based on the variation in subscale scores [1, 2]. As there was no discussion of the target population’s interpretation of the 12 items, there is a lack of evidence for response process validity. The panel found no reported reliability evidence for M-ASSIST data. In terms of relations to other variables, M-ASSIST deep and surface scores were compared to students’ study skills/lecture habits revealing a positive significant correlation between deep scores and favorable study habits (e.g., preparing ahead of time, taking notes in lecture, etc.) [2]. Further, M-ASSIST deep and surface scores have been used in a regression analysis with other variables such as course grade, first-generation status, race/ethnicity, and gender. However, more theoretical support from the literature would help to justify the predictive capabilities of the regression models with these specific variables [2].

References

[1] Bunce, D.M., Komperda, R., Schroeder, M.J., Dillner, D.K. Lin, S., Teichert, M.A., & Hartman, J.R. (2017). Differential use of study approaches by students of different achievement levels. Journal of Chemical Education, 94(10), 1415-1424. https://doi.org/10.1021/acs.jchemed.7b00202

[2] Atieh, E.L., York, D.M., & Muñiz, M.N. (2021). Beneath the surface: An investigation of general chemistry students’ study skills to predict course outcomes. Journal of Chemical Education, 98(2), 281-292. https://doi.org/10.1021/acs.jchemed.0c01074

[3] Frey, R.F., McDaniel, M.A., Bunce, D.M., Cahill, M.J., & Perry, M.D. (2020). Using students’ concept-building tendencies to better characterize average-performing student learning and problem-solving approaches in general chemistry. CBE–Life Sciences Education, 19(3), ar42. https://doi.org/10.1187/cbe.19-11-0240