Jeffrey Bush Tayne

Objectives . Physical computing systems are increasingly being integrated into secondary school science and STEM instruction, yet little is known about how teachers, especially those with little background and experience in computing, help students during the inevitable debugging moments that arise. In this article, we describe a framework, comprising two dimensions, for characterizing how teachers support students as they debug a physical computing system called the Data Sensor Hub (DASH). The DASH enables students to program sensors to measure, analyze, and visualize data as they engage in science inquiry activities. Participants . Five secondary school teachers implemented an inquiry-oriented instructional unit designed to introduce students to working with the DASH as a tool for scientific inquiry. Study Method . Findings drew on video analysis of the teachers’ classroom implementations of the unit. A review of the data corpus led to the selection of 23 moments where the teachers supported an individual or small groups of students engaged in debugging. These moments were analyzed using a grounded perspective based on Interaction Analysis to characterize the teachers’ varied interactional approaches. Findings . Our analysis revealed how teachers’ moves during debugging moments fell along two dimensions. The first dimension characterizes teachers’ positioning during the debugging interactions, ranging from a positioning for teacher understanding to a positioning for student understanding of the bug. The second dimension characterizes the inquiry orientation of the teachers’ questions and guidance, ranging from focusing on the debugging process to focusing on the product—or fixing the bug. Further, teachers’ moves often fell along different points on these dimensions given nuances in the instructional context. Conclusions . The framework offers a first step toward characterizing teachers’ debugging pedagogy as they support students during debugging moments. It also calls attention to how teachers do not necessarily need to be programming experts to effectively help students learn independent and generalizable debugging strategies. Further, it illustrates the variety of expertise that teachers can bring to debugging moments to support students learning to debug. Finally, the framework provides implications for the design of professional learning and supports for teachers as they increasingly are asked to support students in computing—and debugging—activities across a range of disciplines.

The use of Artificial Intelligence (AI) in K-12 education is showing considerable promise to enhance student learning, yet existing tools continue to situate AI tutoring firmly within the context of one-on-one instruction and personalized learning. As HCI, learning science, and team science researchers we envision AI to help students become better collaborators—a highly valued skill for their lives after school. In this demonstration we present “CoBi”—a multi-party AI partner that focuses on the relationship dimension of collaboration. CoBi helps students to co-negotiate classroom agreements along four dimensions: respect, equity, community, and thinking. CoBi then uses state-of-the-art speech and language technologies to look for and visualize evidence of these agreements as they occur during small group student talk. Through these feedback visualizations, students can hone collaboration skills, collaboratively reflect about and identify areas for improvement, and develop critical AI literacy skills.

Rational number and fractions concepts are inherently difficult; and lack of mastery often holds students back from success in subsequent mathematics courses. This paper describes design characteristics of a software based, adaptive, rational number tutor with virtual manipulatives, realistic contexts, and procedural feedback. Then, the paper presents findings from a randomized crossover trial designed to evaluate the impact of the described intervention on student fraction achievement. The trial was conducted in two districts in two states with 17 elementary school teachers and 297 4th and 5th grade students. Half of the participating classrooms replaced worksheet practice time (over 10 instructional hours) with Woot Math Adaptive Learning (WMAL), a digital tutor that incorporates dynamic digital manipulatives, video tutorials and automatic feedback to students and teachers. After 10 instructional hours the groups switched conditions for another 10 instructional hours so each student would have exposure to the treatment and control conditions. Analysis shows that regardless of treatment order, student performance gains on assessment items (mostly from NAEP and TIMMS) were statistically higher, ( d = 0.39, F (1,589) = 5.73, p < 0.05), after 10 days of instruction with WMAL than they were after 10 days of business‐as‐usual instruction. This difference of 0.39 standard units corresponds to an improvement index of 10.9 (percentile point gain compared to non‐treatment). The results demonstrate how the described approach to software and instructional design can work together to support significant increases in student achievement in rational number domains by combining best practices in feedback, curricular design, and adaptive instructional sequences. Practitioner notes: What is already known about this topic? Fraction difficulties are common and compound into greater math difficulties and math anxiety. Best practices for teaching fractions include the use of manipulatives and a focus on conceptual understanding. Feedback should focus on both the process of learning and the products that students produce. Adaptive software systems have the potential to support student practice but there are limited studies in authentic classroom environments with comparable control groups. Other adaptive systems have not implemented best practices in adaptability, design for feedback and curricular design. What this paper adds? Describes a software‐based intervention designed with best practices in curricular design for student development of conceptual understanding of fractions. Describes adaptive features of the software intervention for pacing and automated feedback on both student responses and their work. Reports on a randomised crossover study to evaluate the effectiveness of this intervention as compared to business‐as‐usual instructional methods for student practice time. Implications for practice and/or policy? Provides evidence to support curricular materials that use manipulatives and are designed to promote conceptual understanding in addition to procedural fluency. Describes how technology can efficiently scale best practices and support teachers in helping students make sense of fractions. Reports on how classroom technology can support and extend teaching through personalised learning and improved feedback used during independent practice time.

As teacher professional development efforts continue to scale to meet the growing demand for computer science educators, more individuals with little formal preparation in the discipline are seeking training. For this reason, it is important to understand the kinds of questions that these teachers, along with administrators and IT staff, are asking professional development providers. This research examines questions received by Scalable Game Design (SGD), a project that engages students in computing through game and simulation design activities. SGD has provided training for more than 300 teachers since 2009. We have found several dimensions of interest in the question pool. The major categories of questions received are pedagogical, technical, and procedural, and we present a generalizable taxonomy of question types plus specific examples. In addition, question content and questioner roles fluctuate throughout the professional development and classroom implementation cycle, from initial inquiries to requests regarding next steps. Knowledge of these factors can lead to adjustments in training content to reduce questions later on and potentially increase teacher confidence; moreover, this information can inform planning for support resources, an especially important activity when project growth is forecast. We also discuss how our support structures have changed over the life of the project and compare them to two other curriculum initiatives that rely on unique software environments. Our future work will investigate the characteristics of teachers who are asking particular kinds of questions, including their disciplinary backgrounds, experience in the classroom, familiarity with SGD, and instructional environments.