A Gap Analysis of Noncognitive Constructs in Evaluation Instruments Designed for Computing Education

McGill, Monica M.; Decker, Adrienne; McKlin, Tom; Haynie, Kathy

doi:10.1145/3287324.3287362

Cited by 12 publications

(5 citation statements)

References 21 publications

(22 reference statements)

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“…For each research article, information about the evaluation methods and instruments was recorded. Appropriate evaluation is an area that has been explored by the researchers in the context of this same set of data and discussed in greater detail than presented here [28,29]. How and what was assessed across computing and STEM articles was compared.…”

Section: Discussionmentioning

confidence: 99%

A Systematic Review Exploring the Differences in Reported Data for Pre-College Educational Activities for Computer Science, Engineering, and Other STEM Disciplines

Decker

McGill

2019

Education Sciences

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There has been considerable investment in pre-college educational interventions for all areas of STEM (including computer science). The goal of many of these initiatives is to engage and interest students early in their educational career. In this study, a systematic literature review was undertaken to determine the demographic and program data collected and reported for the field of computing education and for other STEM disciplines for activities that were not designed as part of the formal in-class curriculum (e.g., outreach activities). A comparison-contrast analysis of the resulting 342 articles found similarities and key differences in the reporting of this data as well as overarching characteristics of missing or incomplete reporting across disciplines. Authors from both fields reported equally well in the four categories studied: information about evaluation, participant gender, participant race and/or ethnicity, and activity demographics. However, the computing education articles were more likely to have clearly stated research questions and comparative analysis based on demographic characteristics. They were less likely to include the number of participants in the study, participant age/grade level, socioeconomic status, disability information, location of intervention, and instructor demographics. Through this analysis, it was determined that reporting can be improved across all disciplines to improve the quantity of data needed to replicate studies and to provide complete data sets that provide for the comparison of collected data.

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Section: Discussionmentioning

confidence: 99%

A Systematic Review Exploring the Differences in Reported Data for Pre-College Educational Activities for Computer Science, Engineering, and Other STEM Disciplines

Decker

McGill

2019

Education Sciences

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“…The second construct was motivation, especially intrinsic motivation or labelled as interest (e.g., Deci & Ryan, 1985), due to its strongest effect size for predicting student achievement in Hattie's (2009) mega-analysis over more than 800 meta-analytic studies. Based on the PSCF framework (Lee & Shute, 2010) and McGill et al (2019), the school climate factor expressed in sense of belonging and bullying was also considered in the present study as an important dimension of students' social environment that could affect academic performance. In the following sections, each of the four non-cognitive variables and their relationships to students' achievement were briefly outlined.…”

Section: Introductionmentioning

confidence: 99%

Cross-Country Predictive Validities of Non-cognitive Variables for Mathematics Achievement: Evidence based on TIMSS 2015

Lee

Chen

2019

EURASIA J MATH SCI T

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This study presents empirical findings demonstrating predictive validities of noncognitive variables for mathematics achievement among primary and secondary school students from crosscountry perspectives. Results based on TIMSS 2015 assessment showed that confidence was a moderately strong predictor of mathematics achievement in all TIMSS participant countries (100%). Interest, on the other hand, was a moderately strong predictor in most countries for eighth-graders (77%) but only in about a dozen countries for fourth-graders (20%), showing a stronger interestachievement link for the secondary school students, from the cross-national perspective. The sense of belonging measure demonstrated a lack of its relevance to primary school students' achievement. Further, bullying showed predictive relevance for student achievement only in three countries (South Africa, Jordan, and Egypt). The study concludes that while confidence was a universally relevant predictor of student achievement across all countries/regions, predictive utilities of interest, sense of belonging, and bullying appeared to be heavily dependent on a grade-level and country/regional context.

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“…Concerns have arisen over the last few years about the quality of research that is being conducted on computer science education [1,3,5,6]. There have also been multiple calls within the community to recognize the gaps in research of student participants [4,7].…”

Section: Study Detailsmentioning

confidence: 99%

Building Recommendations for Conducting Equity-Focused, High Quality K-12 Computer Science Education Research

McGill

Heckman

Chytas

et al. 2023

Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education v. 2

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To investigate and identify promising practices in equitable K-12 computer science (CS) education, the capacity for education researchers to conduct this research must be rapidly built globally. Simultaneously, concerns have arisen over the last few years about the quality of research that is being conducted and the lack of equity-focused research.In this working group, we will tackle the research question: In what ways can previous research standards inform high-quality, equity-focused K-12 CS education research?We will use existing research and various standards bodies (e.g., European Educational Research Association, Australian Education Research Organisation, CONSORT, American Psychological Association) to synthesize key features in the context of equity-focused K-12 CS education research. We will then vet these attributes with experts who can provide feedback and refine our recommendations and guidelines. Our working group will select the experts using a strata reflecting a diversity of backgrounds and experiences to support our focus on student populations that have been historically marginalized in computing (e.g., low-income students, rural students, girls, students with disabilities).Our recommendations will directly impact future equitable computing education research by providing guidance on conducting high-quality research such that the findings can be aggregated and impact future policy with evidence-based results. While we recognize that different countries and regions may yield differing answers to this question, our recommendations will be robust enough that Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s).

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A Gap Analysis of Noncognitive Constructs in Evaluation Instruments Designed for Computing Education

Cited by 12 publications

References 21 publications

A Systematic Review Exploring the Differences in Reported Data for Pre-College Educational Activities for Computer Science, Engineering, and Other STEM Disciplines

A Systematic Review Exploring the Differences in Reported Data for Pre-College Educational Activities for Computer Science, Engineering, and Other STEM Disciplines

Cross-Country Predictive Validities of Non-cognitive Variables for Mathematics Achievement: Evidence based on TIMSS 2015

Building Recommendations for Conducting Equity-Focused, High Quality K-12 Computer Science Education Research

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