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As assessment becomes an ever more critical facet of higher education, it is apparent that some faculty do not always value assessment (Crossley & Wang, 2010; Ebersole, 2009). Further, faculty may react with resistance, particularly when they perceive that assessment is being imposed upon them from external sources (Crossley & Wang, 2010; Marrs, 2009; Welsh & Metcalf, 2003). Motivation for faculty to participate in assessment is therefore a critical question. We conducted a qualitative study to explore faculty attitudes towards general education assessment, focusing particularly on faculty motivation for engaging in assessment. General education coordinators were interviewed about their perceptions of student learning outcomes assessment, using a semi-structured interview approach, and then coded by consensus according to Expectancy-Value Theory of motivation (Eccles et al., 1983; Wigfield & Eccles, 2000; Wentzel & Brophy, 2014). Implications for future assessment practice are also shared.

This meta-analysis provides an extensive and organized summary of intervention studies in education that are grounded in motivation theory. We identified 74 published and unpublished papers that experimentally manipulated an independent variable and measured an authentic educational outcome within an ecologically valid educational context. Our analyses included 92 independent effect sizes with 38,377 participants. Our results indicated that interventions were generally effective, with an average mean effect size of d = 0.49 (95% confidence interval = [0.43, 0.56]). Although there were descriptive differences in the effect sizes across several moderator variables considered in our analyses, the only significant difference found was for the type of experimental design, with randomized designs having smaller effect sizes than quasi-experimental designs. This work illustrates the extent to which interventions and accompanying theories have been tested via experimental methods and provides information about appropriate next steps in developing and testing effective motivation interventions in education.

In an article published in "Educational Measurement: Issues and Practice," Gaertner and McClarty (2015) discuss a college readiness index based, in part, on nonacademic or noncognitive factors measured in middle school. Such an index is laudable as it incorporates important constructs beyond academic achievement measures that may be important in assessing college readiness. It also holds potential in identifying areas of need at a critical time and can theoretically inform important interventions that may be necessary prior to the later stages of high school. However, one of the noncognitive factors--motivation--appeared to be theoretically incomplete, underrepresented, and contained items irrelevant to the construct of academic motivation. We offer our concerns about the validity of this factor as measured by the index and the associated implications about the consequences of using this to inform educational interventions. Through this commentary, we hope to offer constructive feedback on future research that can build upon Gaertner and important work.

The term “multilevel meta-analysis” is encountered not only in applied research studies, but in multilevel resources comparing traditional meta-analysis to multilevel meta-analysis. In this tutorial, we argue that the term “multilevel meta-analysis” is redundant since all meta-analysis can be formulated as a special kind of multilevel model. To clarify the multilevel nature of meta-analysis the four standard meta-analytic models are presented using multilevel equations and fit to an example data set using four software programs: two specific to meta-analysis (metafor in R and SPSS macros) and two specific to multilevel modeling (PROC MIXED in SAS and HLM). The same parameter estimates are obtained across programs underscoring that all meta-analyses are multilevel in nature. Despite the equivalent results, not all software programs are alike and differences are noted in the output provided and estimators available. This tutorial also recasts distinctions made in the literature between traditional and multilevel meta-analysis as differences between meta-analyticchoices, not between meta-analyticmodels, and provides guidance to inform choices in estimators, significance tests, moderator analyses, and modeling sequence. The extent to which the software programs allow flexibility with respect to these decisions is noted, with metafor emerging as the most favorable program reviewed. [ABSTRACT FROM PUBLISHER]

As assessment becomes an ever more critical facet of higher education, it is apparent that some faculty do not always value assessment (Crossley & Wang, 2010; Ebersole, 2009). Further, faculty may react with resistance, particularly when they perceive that assessment is being imposed upon them from external sources (Crossley & Wang, 2010; Marrs, 2009; Welsh & Metcalf, 2003). Motivation for faculty to participate in assessment is therefore a critical question. We conducted a qualitative study to explore faculty attitudes towards general education assessment, focusing particularly on faculty motivation for engaging in assessment. General education coordinators were interviewed about their perceptions of student learning outcomes assessment, using a semi-structured interview approach, and then coded by consensus according to Expectancy-Value Theory of motivation (Eccles et al., 1983; Wigfield & Eccles, 2000; Wentzel & Brophy, 2014). Implications for future assessment practice are also shared. [ABSTRACT FROM AUTHOR]