Skip to main content

Attitude Toward The Subject Of Chemistry Inventory V2

ASCI V2

    OVERVIEW
    Overview
    Listed below is general information about the instrument.
    Summary
    Original author(s)
    • Xu, X., & Lewis, J.E.

    Original publication
    • Xu, X., & Lewis, J.E. (2011). Refinement of a chemistry attitude measure for college students. Journal of Chemical Education, 88(5), 561-568.

    Year original instrument was published 2011
    Inventory
    Number of items 8
    Number of versions/translations 2
    Cited implementations 18
    Language
    • English
    Country United States, Australia, Saudi Arabia, Qatar, Philippines
    Format
    • Response Scale
    Intended population(s)
    • Students
    • Undergraduate
    Domain
    • Affective
    Topic
    • Attitutde
    Evidence
    The CHIRAL team carefully combs through every reference that cites this instrument and pulls all evidence that relates to the instruments’ validity and reliability. These data are presented in the following table that simply notes the presence or absence of evidence related to that concept, but does not indicate the quality of that evidence. Similarly, if evidence is lacking, that does not necessarily mean the instrument is “less valid,” just that it wasn’t presented in literature. Learn more about this process by viewing the CHIRAL Process and consult the instrument’s Review (next tab), if available, for better insights into the usability of this instrument.

    Information in the table is given in four different categories:
    1. 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
    2. Reliability - information about the evidence presented to establish reliability of data generated by the instrument; please see the Glossary for term definitions
    3. Validity - information about the evidence presented to establish reliability of data generated by the instrument; please see the Glossary for term definitions
    4. 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 13 14 15 16 17 18

    General

    Original development paper
    Uses the instrument in data collection
    Modified version of existing instrument
    Evaluation of existing instrument

    Reliability

    Test-retest reliability
    Internal consistency
    Coefficient (Cronbach's) alpha
    McDonald's Omega
    Inter-rater reliability
    Person separation
    Generalizability coefficients
    Other reliability evidence

    Vailidity

    Expert judgment
    Response process
    Factor analysis, IRT, Rasch analysis
    Differential item function
    Evidence based on relationships to other variables
    Evidence based on consequences of testing
    Other validity evidence

    Other information

    Difficulty
    Discrimination
    Evidence based on fairness
    Other general evidence
    Review
    DISCLAIMER: The evidence supporting the validity and reliability of the data summarized below is for use of this assessment instrument within the reported settings and populations. The continued collection and evaluation of validity and reliability evidence, in both similar and dissimilar contexts, is encouraged and will support the chemistry education community’s ongoing understanding of this instrument and its limitations.
    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 2)

    (Post last updated June 2, 2021)

    Review panel summary

    The ASCIv2 is an instrument that measures two aspects of students’ attitudes toward chemistry: Intellectual Accessibility and Emotional Satisfaction [1]. It consists of 8 semantic differential items, four on each scale. The instrument has been used in both paper and online formats and the time needed for completion is less than 5 minutes. The instrument has been used in a variety of courses and evidence for the validity and reliability of data from this instrument has been reported from students in general chemistry [1-7, 9-10], organic chemistry [8, 11], and second year inorganic chemistry [12] courses in the United States. Data have also been collected with students in Australia [3, 7, 9], Saudi Arabia [7], and Qatar [10] using the instrument in English throughout.

    Confirmatory factor analysis has been used to produce abundant evidence related to the internal structure [1-4, 7, 11] of data from the instrument. These analyses indicate that the two subscales are robust and function well in multiple settings, although a confirmatory factor analysis of data collected in Saudi Arabia [7] did have poor fit. Two studies conducted student interviews providing limited response process evidence [7, 9] (see recommendations below). The instrument has been used extensively in studies with other measures of affective traits [5] and course achievement [1, 2, 4, 11] providing evidence for relations to other variables validity. Additional evidence for these relations include reports indicating the instrument detecting differences in attitudes of students from one country compared to other countries [3] and in course pedagogy/format [8-10]. Evidence for measurement invariance has been found [11] suggesting that data from the instrument works consistently across student cohorts. There is limited evidence to support test-retest reliability [2, 4]. Evidence for single administration reliability of both subscales is based on coefficient alpha values, ranging from 0.56 – 0.85 [1-10, 11], and omega values of 0.69 – 0.81 [11].

    Recommendations for use

    Given the abundant evidence supporting the proposed internal structure of data from the subscales on the ASCIv2, it can be used to measure two aspects of students’ attitude towards chemistry: Intellectual Accessibility and Emotional Satisfaction. To increase response process validity evidence, additional student interviews are recommended, especially for studies using the instrument with non-native English speakers. For studies seeking to compare attitudes across groups, across time, or in alternate delivery formats, it is recommended that measurement invariance be investigated further.

    Details from panel review

    The internal structure of data from the ASCIv2 has been thoroughly investigated and appears to be well-supported [1-4, 7, 11]. The subscales, while not developed from a strong theoretical stance, have been mapped onto an existing theoretical framework [1, 11]. When data were collected from students in Saudi Arabia [7], the confirmatory factor analysis model fit was not as good, and one item was identified as being problematic. With only two reports of use in non-native English-speaking countries [7, 10], if the instrument is used in this type of setting a thorough investigation of the internal structure and the response process of the data is warranted.

    Student attitudes, on one or both subscales, have been found to positively correlate with ability/achievement [1, 2, 4, 11]. The instrument has also been used to investigate the relation between student attitude and course delivery, with attitudes in a flipped course improving more than in a traditional course [8] and no difference between online versus face-to-face delivery [12]. The instrument has detected higher perceived Intellectual Accessibility from students in courses using POGIL pedagogy compared to students in a traditional course [9, 11].

    Scalar measurement invariance has been found across groups (Black female students versus all other students), thereby supporting the comparison of their ASCIv2 scores [11]. No evidence for configural invariance across time (i.e., pre to post) was found, therefore, the comparison of scores in this manner is currently unsupported [4]. More work in measurement invariance is needed to better understand which comparisons would be supported.

    Evidence for reliability is largely based on reports of coefficient alpha [1-10, 12], with one study reporting a value of omega [11]. While alpha is a widely used measure of single administration reliability, there is no evidence that the data from this instrument meet the criteria for its use [11].

    The instrument has been used in both paper and online administrations. One study indicated that the descriptive statistics did not differ when used online versus paper [2]. However, more work is needed in this area to demonstrate the equivalent functioning of the instrument in these different environments.

    References

    [1] Xu, X., & Lewis, J. E. (2011). Refinement of a chemistry attitude measure for college students. Journal of Chemical Education, 88(5), 561–568. https://doi.org/10.1021/ed900071q

    [2] 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. https://doi.org/10.1039/c1rp90032c

    [3] Xu, X., Southam, D. C., & Lewis, J. E. (2012). Attitude toward the subject of chemistry in Australia: an ALIUS and POGIL collaboration to promote cross-national comparisons. Australian Journal of Education in Chemistry, 72, 32–36.

    [4] Brandriet, A. R., Ward, R. M., & Bretz, S. L. (2013). Modeling meaningful learning in chemistry using structural equation modeling. Chemistry Education Research and Practice, 14(4), 421–430. https://doi.org/10.1039/c3rp00043e

    [5] Chan, J. Y. K., & Bauer, C. F. (2014). Identifying at-risk students in general chemistry via cluster analysis of affective characteristics. Journal of Chemical Education, 91(9), 1417–1425. https://doi.org/10.1021/ed500170x

    [6] Cracolice, M. S., & Busby, B. D. (2015). Preparation for college general chemistry: more than just a matter of content knowledge acquisition. Journal of Chemical Education, 92(11), 1790–1797. https://doi.org/10.1021/acs.jchemed.5b00146

    [7] Xu, X., Alhooshani, K., Southam, D., & Lewis, J. E. (2015). Gathering psychometric evidence for ASCIv2 to support cross-cultural attitudinal studies for college chemistry programs. In Affective Dimensions in Chemistry Education; Kahveci, Orgill, Eds.; Springer-Verlag: Berlin; pp 177–194. https://doi.org/10.1007/978-3-662-45085-7_9

    [8] Mooring, S. R., Mitchell, C. E., & Burrows, N. L. (2016). Evaluation of a flipped, large-enrollment organic chemistry course on student attitude and achievement. Journal of Chemical Education, 93(12), 1972–1983. https://doi.org/10.1021/acs.jchemed.6b00367

    [9] Vishnumolakala, V. R., Southam, D. C., Treagust, D. F., Mocerino, M., & Qureshi, S. (2017). Students’ attitudes, self-efficacy and experiences in a modified process-oriented guided inquiry learning undergraduate chemistry classroom. Chemistry Education Research and Practice, 18(2), 340–352. https://doi.org/10.1039/c6rp00233a

    [10] Vishnumolakala, V. R., Qureshi, S. S., Treagust, D. F., Mocerino, M., Southam, D. C., & Ojeil, J. (2018). Longitudinal impact of process-oriented guided inquiry learning on the attitudes, self-efficacy and experiences of pre-medical chemistry students. Qscience Connect, 2018(1), 1. https://doi.org/10.5339/connect.2018.1

    [11] Rocabado, G. A., Kilpatrick, N. A., Mooring, S. R., & Lewis, J. E. (2019). Can we compare attitude scores among diverse populations? An exploration of measurement invariance testing to support valid comparisons between black female students and their peers in an organic chemistry course. Journal of Chemical Education, 96(11), 2371–2382. https://doi.org/10.1021/acs.jchemed.9b00516

    [12] Nennig, H. T., Idárraga, K. L., Salzer, L. D., Bleske-Rechek, A., & Theisen, R. M. (2019). Comparison of student attitudes and performance in an online and a face-to-face inorganic chemistry course. Chemistry Education Research and Practice, 21(1), 168–177. https://doi.org/10.1039/c9rp00112c

    Versions
    Listed below are all versions and modifications that were based on this instrument or this instrument were based on.
    Instrument is derived from:
    Name Authors
    • Bauer, C.F.

    Citations
    Listed below are all literature that develop, implement, modify, or reference the instrument.
    1. Xu, X., & Lewis, J.E. (2011). Refinement of a chemistry attitude measure for college students. Journal of Chemical Education, 88(5), 561-568.

    2. Nennig, H.T., Idarraga, K.L., Salzer, L.D., Bleske-Rechek, A., & Theisen, R.M. (2020). Comparison of student attitudes and performance in an online and a face-to-face inorganic chemistry course. Chemistry Education Research and Practice, 21(1), 168-177.

    3. Underwood, S.M., Reyes-Gastelum, D., & Cooper, M.M. (2016). When do students recognize relationships between molecular structure and properties? A longitudinal comparison of the impact of traditional and transformed curricula. Chemistry Education Research

    4. Xu, X., Southam, D., & Lewis, J. (2012). Attitude toward the subject of chemistry in Australia: An ALIUS and POGIL collaboration to promote cross-national comparisons. Australian Journal of education in Chemistry, 72, 32-36.

    5. Cracolice, M.S., & Busby, B.D. (2015). Preparation for College General Chemistry: More than Just a Matter of Content Knowledge Acquisition. Journal of Chemical Education, 92(11), 1790-1797.

    6. Xu, X., Villafañe, S.M., & Lewis, J.E. (2013). College students' attitudes toward chemistry, conceptual knowledge and achievement: Structural equation model analysis. Chemistry Education Research and Practice, 14(2), 188-200.

    7. Griep, M. A., Stains, M., & Velasco, J. (2018). Coordination of the Chemistry REU Program at the University of Nebraska− Lincoln. In Best Practices for Chemistry REU Programs (pp. 139-156). American Chemical Society.

    8. Stanich, C.A., Pelch, M.A., Theobald, E.J., & Freeman, S. (2018). A new approach to supplementary instruction narrows achievement and affect gaps for underrepresented minorities, first-generation students, and women. Chemistry Education Research and Pract

    9. Mooring, S.R., Mitchell, C.E., & Burrows, N.L. (2016). Evaluation of a Flipped, Large-Enrollment Organic Chemistry Course on Student Attitude and Achievement. Journal of Chemical Education, 93(12), 1972-1983.

    10. 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.

    11. Brandriet, A.R., Ward, R.M., & Bretz, S.L. (2013). Modeling meaningful learning in chemistry using structural equation modeling. Chemistry Education Research and Practice, 14(4), 421-430.

    12. Vishnumolakala, V.R., Southam, D.C., Treagust, D.F., Mocerino, M., & Qureshi, S. (2017). Students' attitudes, self-efficacy and experiences in a modified process-oriented guided inquiry learning undergraduate chemistry classroom. Chemistry Education Resea

    13. Chan, J.Y.K., & Bauer, C.F. (2016). Learning and studying strategies used by general chemistry students with different affective characteristics. Chemistry Education Research and Practice, 17(4), 675-684.

    14. Xu, X., Alhooshani, K., Southam, D., & Lewis, J. E. (2015). Gathering psychometric evidence for ASCIv2 to support cross-cultural attitudinal studies for college chemistry programs. In Affective dimensions in chemistry education (pp. 177-194). Springer, Berlin, Heidelberg.

    15. Chan, J.Y.K., & Bauer, C.F. (2014). Identifying at-risk students in general chemistry via cluster analysis of affective characteristics. Journal of Chemical Education, 91(9), 1417-1425.

    16. Vishnumolakala, V. R., Qureshi, S. S., Treagust, D. F., Mocerino, M., Southam, D. C., & Ojeil, J. (2018). Longitudinal impact of process-oriented guided inquiry learning on the attitudes, self-efficacy and experiences of pre-medical chemistry students. QS

    17. Damo, K. L., & Prudente, M. S. (2019, January). Investigating students' attitude and achievement in organic chemistry using interactive application. In Proceedings of the 10th International Conference on E-Education, E-Business, E-Management and E-Learning (pp. 36-41).

    18. Rocabado, G.A., Kilpatrick, N.A., Mooring, S.R., & Lewis, J.E. (2019). Can We Compare Attitude Scores among Diverse Populations? An Exploration of Measurement Invariance Testing to Support Valid Comparisons between Black Female Students and Their Peers in