Active learners’ characterization in MOOC forums and their generated knowledge

This study explores and characterizes learners' participation patterns in MOOC forums, as well as the factors that correlate with learners' participation. Educational data mining and learning analytics methods were used to retrieve and analyze the learners' interpersonal interaction data, which had accumulated in the Coursera log files. The content in the forums was categorized based on Henri's criteria and converted into quantitative values that could be compared and visualized. It was found that only 20% of the learners were collaborating in the forums throughout the entire course and were responsible for 50% of the total posts. A portion of them earned the name “Super Active.” The analyses not only demonstrated the volume of activity and its pattern but also revealed the content of the discussions, which helped to highlight the needs and reasons for students' usage of the forums. The content analysis showed intensity in the “Cognitive” and “Discipline” categories. Thus, forum participants benefit from discussions not only socially but disciplinarily and cognitively as well. Furthermore, even though a strong significant correlation was found between the learners’ completion status and their activity in the forums, a group of learners, who did not complete the course, was highly active.     

Effects of Linking Methods on Detection of DIF

Studies of differential item functioning under item response theory require that item parameter estimates be placed on the same metric before comparisons can be made. The present study compared the effects of three methods for linking metrics: a weighted mean and sigma method (WMS); the test characteristic curve method (TCC); and the minimum chi-square method (MCS), on detection of differential item functioning. Both iterative and noniterative linking procedures were compared for each method. Results indicated that detection of differentially functioning items following linking via the test characteristic curve method gave the most accurate results when the sample size was small. When the sample size was large, results for the three linking methods were essentially the same. Iterative linking provided an improvement in detection of differentially functioning items over noniterative linking particularly with the .05 alpha level. The weighted mean and sigma method showed greater improvement with iterative linking than either the test characteristic curve or minimum chi-square method.     

Students’ experiences of supervision in academic and industry settings: results of an Australian study

The joint supervision of Research Higher Degree (RHD) students by an industry and university supervisor is likely to increase in forthcoming years with a rise in the number of university–industry collaborations. Research students may become involved in these collaborative arrangements for a variety of reasons and may launch into their RHD without considering how they will serve two masters, and how this complex relationship will affect their RHD experience. Moreover, little research has been conducted to assess the impact of these arrangements on current RHD students’ experiences. The experiences of students with academic and industry supervisors were, therefore, explored in a survey of confirmed RHD students at an Australian research‐intensive university. This paper investigates whether RHD students conducting research in traditional academic settings have a different experience to students working on industry‐related projects in industry settings, specifically in regards to supervision and institutional access and engagement.     

Investigating the Effect of Item Position in Computer‐Based Tests

Computer‐based tests (CBTs) often use random ordering of items in order to minimize item exposure and reduce the potential for answer copying. Little research has been done, however, to examine item position effects for these tests. In this study, different versions of a Rasch model and different response time models were examined and applied to data from a CBT administration of a medical licensure examination. The models specifically were used to investigate whether item position affected item difficulty and item intensity estimates. Results indicated that the position effect was negligible.     

Inferring cross sections of 3D objects: A new spatial thinking test

A new spatial ability test was administered online to 223 undergraduate students enrolled in introductory science courses. The 30-item multiple choice test measures individual differences in ability to identify the two-dimensional cross section of a three-dimensional geometric solid, a skill that has been identified as important in science, technology, engineering and mathematics (STEM) fields. Bivariate and partial correlations suggest that the test measures a skill that is distinct from three-dimensional mental rotation and change in view perspective. Test items varied along two scales: complexity of the geometric solid to be sliced and orientation of the cutting plane. Internal reliability of both the overall test and its subscales was satisfactory. Performance was higher on figures cut by orthogonal, rather than oblique, planes. Patterns of performance across more and less complex items, and patterns of sex differences on these items, suggest that items on the test are differentially amenable to imagistic and analytic strategies, with males outperforming females on items that are less amenable to analytic strategies. The test shows promise for online administration and for adaptation to younger populations.     

Bioinformatics Education in High School: Implications for Promoting Science,Technology, Engineering,and Mathematics Careers

We investigated the effects of our Bio-ITEST teacher professional development model and bioinformatics curricula on cognitive traits (awareness, engagement, self-efficacy, and relevance) in high school teachers and students that are known to accompany a developing interest in science, technology, engineering, and mathematics (STEM) careers. The program included best practices in adult education and diverse resources to empower teachers to integrate STEM career information into their classrooms. The introductory unit, Using Bioinformatics: Genetic Testing, uses bioinformatics to teach basic concepts in genetics and molecular biology, and the advanced unit, Using Bioinformatics: Genetic Research, utilizes bioinformatics to study evolution and support student research with DNA barcoding. Pre–post surveys demonstrated significant growth (n = 24) among teachers in their preparation to teach the curricula and infuse career awareness into their classes, and these gains were sustained through the end of the academic year. Introductory unit students (n = 289) showed significant gains in awareness, relevance, and self-efficacy. While these students did not show significant gains in engagement, advanced unit students (n = 41) showed gains in all four cognitive areas. Lessons learned during Bio-ITEST are explored in the context of recommendations for other programs that wish to increase student interest in STEM careers.