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The scarcity of efficient and user-friendly authoring tools has long been acknowledged as a limiting factor in the widespread development and deployment of intelligent tutoring systems (ITSs). Creating an effective authoring tool for domain experts poses two significant challenges: it must facilitate the creation of curricular content by domain experts who are typically neither ITS experts nor software engineers, and it must support the creation or modification of ITS-specific pedagogical strategies without exposing the complexity of the ITS itself to the domain expert.

Real-time formative assessment of student learning has become the subject of increasing attention. Students’ textual responses to short answer questions offer a rich source of data for formative assessment. However, automatically analyzing textual constructed responses poses significant computational challenges, and the difficulty of generating accurate assessments is exacerbated by the disfluencies that occur prominently in elementary students’ writing. With robust text analytics, there is the potential to accurately analyze students’ text responses and predict students’ future success.

Mining learner generated sketches holds significant potential for acquiring deep insight into learners’ mental models. Drawing has been shown to benefit both learning outcomes and engagement, and learners’ sketches offer a rich source of diagnostic information. Unfortunately, interpreting learners’ sketches—even sketches comprised of semantically grounded symbols—poses significant computational challenges.

This paper explores how robotics can be used as a new educational tool in a Montessori early education classroom. It presents a case study of one early educator’s experience of designing and implementing a robotics curriculum integrated with a social science unit in her mixed-age classroom. This teacher had no prior experience using robotics in the classroom beyond a three-day professional development workshop. The case study was constructed by collecting data from surveys, interviews, and a personal blog written by the teacher documenting her experience.

This paper employs meta-analysis to determine the influence of computer-based scaffolding characteristics and study and test scorequality on cognitive outcomes in science, technology, engineering, and mathematics education at the secondary, college, graduate, and adult levels.

Argumentation is central to instruction centered on socio-scientific issues (Sadler & Donnelly in International Journal of Science Education, 28(12), 1463–1488, 2006. doi:10.1080/09500690600708717). Teachers can play a big role in helping students engage in argumentation and solve authentic scientific problems. To do so, they need to learn one-to-one scaffolding—dynamic support to help students accomplish tasks that they could not complete unaided.

Mejia Colindres, C. A. (2015). Thunder and Lightning: Understanding Equidistance. Mathematics Teacher, 108(6), 454-460.

Sorto, M. A., Mejia Colindres, C. A., & Wilson, A. T. (2014). Uncovering and Eliciting Mathematical Perceptions in Linguistically Diverse Classrooms. Mathematics Teaching in the Middle School, 20(2), 72–77.

From the perspectives of Graduate Research Assistants (GRAs), this study examines the design and implementation of a simulated teaching environment in Second Life (SL) for prospective teachers to teach algebra for diverse learners. Drawing upon the Learning-for-Use framework, the analyses provide evidence on the development of student avatars in construction and role-playing activities. The study reveals challenges, procedures, and suggestions for future simulations. This study also calls for research efforts toward preparing mathematics teachers for cultural diversity.

Recent reform efforts and the next generation science standards emphasize the importance of incorporating authentic scientific practices into science instruction. Modeling can be a particularly challenging practice to address because modeling occurs within a socially structured system of representation that is specific to a domain. Further, in the process of modeling, experts interact deeply with domain-specific content knowledge and integrate modeling with other scientific practices in service of a larger investigation.