Psychometric reevaluation of the scientific attitude inventory‐revised (SAI‐II)

The central purposes of this study were to review the development and evolution of the Scientific Attitude Inventory (SAI) and then reevaluate the psychometric properties of the revised form of the SAI, the Scientific Attitude Inventory II (SAI‐II). The SAI‐II was administered to a convenience sample of 543 middle and high school students from five teachers in four schools in four school districts in San Antonio, Texas, at the beginning of the 2004–2005 school year. Confirmatory factor analysis on the full data set failed to support the existence of a 12‐factor structure (as proposed by the scale developers) or a one‐factor structure. The data were then randomly divided into exploratory [exploratory factor analysis (EFA)] validation and confirmatory [confirmatory factor analysis (CFA)] cross‐validation sets. Exploratory and confirmatory models yielded a three‐factor solution that did not fit the data well [χ² (321) = 646, p < .001; RMSEA = .061 (.90 CI = .054–.068); and CFI = .81]. The three factors were labeled “Science is About Understanding and Explaining” (13 items), “Science is Rigid” (6 items), and “I Want to Be a Scientist” (8 items). The α‐coefficients for these three factors ranged from 0.59 to 0.85. Whether these identified subscales are valid will require independent investigation. In this sample, and consistent with prior publications, the SAI‐II in its current form did not have satisfactory psychometric properties and cannot be recommended for further use. © 2008 Wiley Periodicals, Inc. J Res Sci Teach 45: 600–616, 2008     

Forming an effective partnership with a dedicated LabAssistant: A software shell for engineering laboratory exercises

This paper describes the structure and use of LabAssistant, a software shell purposely written to run alongside engineering laboratory exercises and provide support to students undertaking the exercises. The structure of LabAssistant enables tutors to deliver their own laboratory sessions within the shell using only basic spreadsheet skills. LabAssistant is intended to be used in conjunction with in-depth, analytical laboratory exercises and its features include text entry, numerical input and checking (including verification of calculated values and provision of appropriate feedback), graph sketching, data plotting and report generation. Feedback from students confirms that LabAssistant has enhanced the learning experience, encouraging active engagement, building confidence and assisting progression through the exercise, even using the data and information input during the session to generate the majority of their laboratory write-up automatically. From the tutor's perspective, the provision of immediate and continual help to the students is a significant enhancement to the quality of the learning experience. LabAssistant complements the tutor who is now able to deal effectively with deeper conceptual difficulties and larger student numbers. The facility to verify all calculated values and the creation of a report in a standard electronic format are significant aids to the marking of student submissions.