Based on a framework of computational thinking (CT) adapted from Computer Science Teacher Association's standards, an instrument was developed to assess fifth grade students' CT. The items were contextualized in two types of CT application (coding in robotics and reasoning of everyday events). The instrument was administered as a pre and post measure in an elementary school where a new humanoid robotics curriculum was adopted by their fifth grade. Results show that the instrument has good psychometric properties and has the potential to reveal student learning challenges and growth in terms of CT.

This study describes the impact of embedding dynamic computer visualization (DCV) in an online instrument that was designed to assess students' understanding of osmosis. The randomized posttest-only control group research was designed to compare the effect and the perceived helpfulness of the integration of DCV before and after the administration of an osmosis instrument. College students from three large classes (N = 640) were randomly assigned to participate in the research through an online system. Rasch-PCM was applied to determine the psychometric properties of the instrument and differentiate the student's understanding of osmosis. Welch two-sample t test was applied to examine whether there was significant discrepancy between groups. Multiple regressions analysis was conducted to evaluate the association between predictors and the student's understanding level, alluding to the performance on the online instrument. We found (a) the psychometric properties of the instrument with DCVs were reliable with good construct validity, (b) students who viewed DCV before they took the assessment performed better than those without, especially on solvation-related items, (c) students' time spent on the DCVs significantly contributed to their performance, (d) the current data analytics enabled us to study respondents' DCV navigation behavior, and (e) we summarized how participants perceived DCVs that are in the assessment. Educational implications and significance of this study is also discussed.

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We present a package of annotation resources, including annotation guideline, flowchart, and an Intelligent Tutoring System for training human annotators. These resources can be used to apply Rhetorical Structure Theory (RST) to essays written by students in K-12 schools. Furthermore, we highlight the great potential of using RST to provide automated feedback for improving writing quality across genres.