ASCI V1
OVERVIEW
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Original author(s) |
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Original publication |
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Year original instrument was published | 2008 |
Inventory | |
Number of items | 20 |
Number of versions/translations | 4 |
Cited implementations | 12 |
Language |
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Country | United States, Fiji, Australia |
Format |
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Intended population(s) |
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Domain |
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Topic |
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EVIDENCE
Information in the table is given in four different categories:
- General - information about how each article used the instrument:
- Original development paper - indicates whether in which paper(s) the instrument was developed initially
- Uses the instrument in data collection - indicates whether an article administered the instrument and collected responses
- Modified version of existing instrument - indicates whether an article has modified a prior version of this instrument
- Evaluation of existing instrument - indicates whether an article explicitly provides evidence that attempt to evaluate the performance of the instrument; lack of a checkmark here implies an article that administered the instrument but did not evaluate the instrument itself
- Reliability - information about the evidence presented to establish reliability of data generated by the instrument; please see the Glossary for term definitions
- Validity - information about the evidence presented to establish reliability of data generated by the instrument; please see the Glossary for term definitions
- Other Information - information that may or may not directly relate to the evidence for validity and reliability, but are commonly reported when evaluating instruments; please see the Glossary for term definitions
Publications: | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 |
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Uses the instrument in data collection | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ||||
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Evaluation of existing instrument | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | |||||
Reliability |
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Test-retest reliability | ✔ | ✔ | ✔ | |||||||||
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Coefficient (Cronbach's) alpha | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | |||||
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Validity |
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Factor analysis, IRT, Rasch analysis | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ||||||
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Evidence based on relationships to other variables | ✔ | ✔ | ||||||||||
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REVIEW
This review was generated by a CHIRAL review panel. Each CHIRAL review panel consists of multiple experts who first individually review the citations of the assessment instrument listed on this page for evidence in support of the validity and reliability of the data generated by the instrument. Panels then meet to discuss the evidence and summarize their opinions in the review posted in this tab. These reviews summarize only the evidence that was discussed during the panel which may not represent all evidence available in the published literature or that which appears on the Evidence tab.
If you feel that evidence is missing from this review, or that something was documented in error, please use the CHIRAL Feedback page.
Panel Review: Attitude toward the Subject of Chemistry Inventory (Version 1)
(Post last updated June 2, 2021)
Review panel summary
The ASCI V1 is a twenty-item semantic differential instrument designed to measure student attitudes toward chemistry. The original design of the instrument does not describe underlying latent characteristics that informed item development. The internal structure of ASCI V1 data has been proposed via exploratory factor analysis, but the structure has varied in the literature and has not yet accounted for all the items in the instrument [1-4, 6]. Factors generated by exploratory factor analysis have shown acceptable internal consistency [1-7] and test-retest reliability over a time-period of up to one week [1, 2, 7]. The attitude scores derived from the instrument have been related to other variables including: chemistry course grades and experience within a chemistry curriculum [1], comparing students across institutions [4] and students receiving different pedagogies [5]. Studies using the ASCI have found inconsistencies in the change in introductory students’ perceived anxiety over the course of the semester with one study reporting a decrease in anxiety [1] and another study reporting an increase [5]. Ultimately, with an unclear internal structure for data from the ASCI V1, its subscales and subsequent use have been varied in the research literature and consistency in subscales across the literature has not been established.
Recommendations for use
The ASCI V1 offers a measure of student attitudes that can be administered to students quickly, however the internal structure of the ASCI V1 data is not yet supported, and a description of the underlying latent characteristics measured has not been advanced yet. As these characteristics determine the meaning of the item groupings and score interpretations, users would be advised to provide further examination of the internal structure of the data generated.
Details from panel review
The ASCI V1 is intended to measure student attitudes using a twenty-item semantic differential that takes most students less than 10 minutes to complete [1]. The original development of the instrument did not cite specific dimensions of attitude that the instrument intended to measure and relied on exploratory factor analysis (principal component analysis) and assigning descriptions to the set of items loading on each factor [1]. The number of factors were identified by eigenvalues greater than 1 which led to three factors with 15 items that had clear loadings on each. The remaining items featured one independent item and four items that cross loaded on multiple factors. Given a missing delineation of attitude constructs in the design along with an exploratory factor analysis not differentiating all items, the internal structure of the instrument is not yet well defined. Subsequent uses of the instrument have also relied on exploratory factor analysis and found that the procedure did not identify clean factors [2], found three factors that differed from the developer [3] or identified a two-factor solution [4, 6, 7]. Ross and colleagues [7] proposed a theoretical framework of attitude hierarchy that utilizes a subset of the items, and which was supported by a partial least squares-structural equation model.
The attitude subscales suggested by the exploratory factor analysis have been related to other variables. The intellectual accessibility subscale has shown a moderate correlation (0.39) with course grades and the other subscales had small correlation values matching expected trends (interest and utility correlated 0.18; anxiety correlated -0.20) [1]. Further, students serving as student leaders in chemistry and chemistry majors have shown higher interest and utility and emotional satisfaction and lower anxiety than introductory chemistry students [1]. Over the course of one semester of first-year chemistry, students’ rating of anxiety was found to decrease in one study [1] but increase in a separate study [5]. The instrument has also demonstrated differences in reported attitude scores between students at different institutions [4] and did not demonstrate differences in reported attitude scores between students receiving different pedagogies at the same institution [5]. The attitude subscales have also shown acceptable single administration reliability with studies reporting a coefficient alpha value greater than 0.7 [1, 2, 4, 5, 7] or close to 0.7 [3, 6]. The subscales have also shown test-retest reliability with correlation values of 0.9 when given in the same setting [2] or correlation values of approximately 0.7 when given one week apart [1, 7].
References
[1] Bauer, C.F. (2008). Attitude towards chemistry: a semantic differential instrument for assessing curriculum impacts. Journal of Chemical Education, 85(10), 1440. https://doi.org/10.1021/ed085p1440
[2] Xu, X., & Lewis, J.E. (2011). Refinement of a chemistry attitude measure for college students. Journal of Chemical Education, 88(5), 561. https://doi.org/10.1021/ed900071q
[3] Brown, S.J., Sharma, B.N., Wakeling, L., Naiker, M., Chandra, S., Gopalan, R.D., & Bilimoria, V.B. (2014). Quantifying attitude to chemistry in students at the University of the South Pacific. Chemistry Education Research and Practice, 15, 184-191. https://doi.org/10.1039/C3RP00155E
[4] Brown, S., Wakeling, L., Peck, B., Naiker, M., Hill, D., & Naidu, K. (2014). Attitude to the subject of chemistry in undergraduate nursing students at Fiji National University and Federation University, Australia. Collegian, 22(4), 369-375. https://doi.org/10.1016/j.colegn.2014.06.001
[5] Chan, J.Y.K, & Bauer, C.F. (2015). Effect of Peer-Led Team Learning (PLTL) on student achievement, attitude, and self-concept in college general chemistry in randomized and quasi experimental designs. Journal of Research in Science Teaching, 52, 319. https://doi.org/10.1002/tea.21197
[6] Brown, S.J., & Naiker, M. (2018). Attitude to the subject of chemistry in nursing and health science undergraduate students. International Journal of Innovation and Research in Educational Science, 5(2), 192-196.
[7] Ross, J., Nuñez, L., & Lai, C.C. (2018). Partial least squares structural equation modeling of chemistry attitude in introductory college chemistry. Chemistry Education Research and Practice, 19, 1270-1286. https://doi.org/10.1039/C7RP00238F
VERSIONS
Name | Authors |
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Attitude Toward The Subject Of Chemistry Inventory V2 |
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Attitude Toward Chemistry Instruments Inventory |
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Modified Chemistry Laboratory Anxiety Instrument |
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CITATIONS
Bauer, C.F. (2008). Attitude towards chemistry: A semantic differential instrument for assessing curriculum impacts. Journal of Chemical Education, 85(10), 1440-1445.
Griep, M. A., Stains, M., Malina, E., & Velasco, J. (2013). Renovating Four General Chemistry Laboratory Rooms at the University of Nebraska-Lincoln. In Innovations and renovations: Designing the teaching laboratory (pp. 75-90). American Chemical Society.
Brandriet, A.R., Xu, X., Bretz, S.L., & Lewis, J.E. (2011). Diagnosing changes in attitude in first-year college chemistry students with a shortened version of Bauer's semantic differential. Chemistry Education Research and Practice, 12(2), 271-278.
Winkelmann, K., Keeney-Kennicutt, W., Fowler, D., Lazo, Macik M., Perez, Guarda P., & Joan, Ahlborn C. (2020). Learning gains and attitudes of students performing chemistry experiments in an immersive virtual world. Interactive Learning Environments, 28(5
Chase, A., Pakhira, D., & Stains, M. (2013). Implementing process-oriented, guided-inquiry learning for the first time: Adaptations and short-term impacts on students’ attitude and performance. Journal of Chemical Education, 90(4), 409-416.
Brown, S.J., Sharma, B.N., Wakeling, L., Naiker, M., Chandra, S., Gopalan, R.D., & Bilimoria, V.B. (2014). Quantifying attitude to chemistry in students at the University of the South Pacific. Chemistry Education Research and Practice, 15(2), 184-191.
Brown, S., & Naiker, M. (2018). Attitude to the subject of chemistry in nursing and health science undergraduate students. International Journal of Innovation and Research in Educational Sciences, 5(2), 192-1965.
Chan, J.Y.K., & Bauer, C.F. (2015). Effect of Peer-Led Team Learning (PLTL) on student achievement, attitude, and self-concept in college general chemistry in randomized and quasi experimental designs. Journal of Research in Science Teaching, 52(3), 319-3
Brown, S., Wakeling, L., Peck, B., Naiker, M., Hill, D., & Naidu, K. (2015). Attitude to the subject of chemistry in undergraduate nursing students at Fiji National University and Federation University, Australia. Collegian, 22(4), 369-375.
Xu, X., & Lewis, J.E. (2011). Refinement of a chemistry attitude measure for college students. Journal of Chemical Education, 88(5), 561-568.
Ross, J., Nunez, L., & Lai, C.C. (2018). Partial least squares structural equation modeling of chemistry attitude in introductory college chemistry. Chemistry Education Research and Practice, 19(4), 1270-1286.
Ross, J., Guerra, E., & Gonzalez-Ramos, S. (2020). Linking a hierarchy of attitude effect to student engagement and chemistry achievement. Chemistry Education Research and Practice, 21(1), 357-370.