Training self-assessment and task-selection skills: A cognitive approach to improving self-regulated learning

For self-regulated learning to be effective, students need to be able to accurately assess their own performance on a learning task and use this assessment for the selection of a new learning task. Evidence suggests, however, that students have difficulties with accurate self-assessment and task selection, which may explain the poor learning outcomes often found with self-regulated learning. In experiment 1, the hypothesis was investigated and confirmed that observing a human model engaging in self-assessment, task selection, or both could be effective for secondary education students’ (N = 80) acquisition of self-assessment and task-selection skills. Experiment 2 investigated and confirmed the hypothesis that secondary education students’ (N = 90) acquisition of self-assessment and task-selection skills, either through examples or through practice, would enhance the effectiveness of self-regulated learning. It can be concluded that self-assessment and task-selection skills indeed play an important role in self-regulated learning and that training these skills can significantly increase the amount of knowledge students can gain from self-regulated learning in which they choose their own learning tasks.     

Cultural differences in the perception of critical interaction behaviors in global virtual teams

We investigated whether members of virtual teams from the U.S., India, and Belgium perceived the same interaction behaviors to be critical for team functioning as Dutch members from an earlier study. Thirteen virtual team workers from the U.S., 11 from India, and 11 from Belgium were interviewed by means of the Critical Incident Technique Flanagan [Flanagan, J. C. (1954). The critical incident technique. Psychological Bulletin, 51, 327–358]. The total number of critical incidents from all countries was 493 and most incidents could be grouped into the same 13 categories as those found in the original Dutch study. However, the results showed that the distributions of the critical incidents from the American, Indian, and Belgian respondents differed from those of the Dutch. Indian and Belgian respondents also mentioned a new category of critical incidents: Respectfulness. The cultural differences were interpreted by means of Hofstede's [Hofstede, G. (2001). Cultures consequences: comparing values, behaviors, institutions, and organizations across nations (2nd ed.). Thousand Oaks, California, U.S.: SAGE Publications] dimensions.     

Breaking the filter bubble: democracy and design

It has been argued that the Internet and social media increase the number of available viewpoints, perspectives, ideas and opinions available, leading to a very diverse pool of information. However, critics have argued that algorithms used by search engines, social networking platforms and other large online intermediaries actually decrease information diversity by forming so-called “filter bubbles”. This may form a serious threat to our democracies. In response to this threat others have developed algorithms and digital tools to combat filter bubbles. This paper first provides examples of different software designs that try to break filter bubbles. Secondly, we show how norms required by two democracy models dominate the tools that are developed to fight the filter bubbles, while norms of other models are completely missing in the tools. The paper in conclusion argues that democracy itself is a contested concept and points to a variety of norms. Designers of diversity enhancing tools must thus be exposed to diverse conceptions of democracy.     

Better Together: Responsive Community Programming at the U-M Library

In the past seven years, the University of Michigan Library's programming model has evolved to be responsive and reflective of staffing areas of interest and expertise. Our team-based, iterative model enables us to develop responsive exhibits, workshops, experiences, and events in our community. This article explores our experiences in developing this model through the lens of some of our collaborations with the Ann Arbor District Library (AADL). Our approach to programming opportunities builds on learning by doing, building deeper, mutually beneficial relationships with other organizations, and continually making sure we are truly developing programming with our audience (our community) in mind. While public and academic libraries often develop distinct sets of services, collections, and expertise to serve their respective communities, successful collaborations can yield interesting opportunities for more effective engagement and programming. Our relationship with AADL has helped us to identify and better understand how we can connect our teaching and research missions with the interests and needs of the broader community in which we are situated.     

Differential Susceptibility in Early Literacy Instruction Through Computer Games: The Role of the Dopamine D4 Receptor Gene (DRD4)

Not every child seems equally susceptible to the same parental, educational, or environmental influences even if cognitive level is similar. This study is the first randomized controlled trial to apply the differential susceptibility paradigm to education in relation to children's genotype and early literacy skills. A randomized pretest–posttest control group design was used to examine the effects of the Intelligent Tutoring System Living Letters. Two intervention groups were created, 1 receiving feedback and 1 completing the program without feedback, and 1 control group. Carriers of the long variant of the dopamine D4 receptor gene (DRD4 7‐repeat) profited most from the computer program with positive feedback, whereas they performed at the lowest level of early literacy skills in the absence of such feedback. Our findings suggest that behind modest overall educational intervention effects a strong effect on a subgroup of susceptible children may be hidden.     

David F. Treagust: congenial soul, science educator, and international research leader

For almost a half century David F. Treagust has been an exemplary science educator who has contributed through his dedication and commitments to students, curriculum development and collaboration with teachers, and cutting edge research in science education that has impacted the field globally, nationally and locally. A hallmark of his outstanding career is his collaborative style that inspires others to produce their best work.     

Estimation of a Nonlinear Intervention Phase Trajectory for Multiple-Baseline Design Data

A multilevel logistic model for estimating a nonlinear trajectory in a multiple-baseline design is introduced. The model is applied to data from a real multiple-baseline design study to demonstrate interpretation of relevant parameters. A simple change-in-levels (ΔLevels) model and a model involving a quadratic function (Quadratic) for the nonlinear intervention phase data were also estimated. In addition, a simulation study was conducted to assess Markov chain Monte Carlo estimation of the logistic model and compare its trajectory recovery with use of the ΔLevels and Quadratic models. While most of the logistic model's parameter values were recovered well, trajectory recovery was very reasonable using the simpler Quadratic model. Results are discussed along with recommendations for practitioners and directions for future research.