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Computing Education Research (CER) is critical for supporting the increasingnumber of students who need to learn computing skills. To systematicallyadvance knowledge, publications must be clear enough to support replications,meta-analyses, and theory-building. The goal of this study is to characterizethe reporting of empiricism in CER literature by identifying whetherpublications include information to support replications, meta-analyses, andtheory building. The research questions are: RQ1) What percentage of papers inCER venues have empirical evaluation? RQ2) What are the characteristics of theempirical evaluation? RQ3) Do the papers with empirical evaluation followreporting norms (both for inclusion and for labeling of key information)? Weconducted an SLR of 427 papers published during 2014 and 2015 in five CERvenues: SIGCSE TS, ICER, ITiCSE, TOCE, and CSE. We developed and applied theCER Empiricism Assessment Rubric. Over 80% of papers had some form of empiricalevaluation. Quantitative evaluation methods were the most frequent. Papers mostfrequently reported results on interventions around pedagogical techniques,curriculum, community, or tools. There was a split in papers that had some typeof comparison between an intervention and some other data set or baseline. Manypapers lacked properly reported research objectives, goals, research questions,or hypotheses, description of participants, study design, data collection, andthreats to validity. CER authors are contributing empirical results to theliterature; however, not all norms for reporting are met. We encourage authorsto provide clear, labeled details about their work so readers can use themethodologies and results for replications and meta-analyses. As our communitygrows, our reporting of CER should mature to help establish computing educationtheory to support the next generation of computing learners.

A Systematic Literature Review of Empiricism and Norms of Reporting in Computing Education Research Literature