The Next Generation Science Standards [1] recognized evidence-based argumentation as one of the essential skills for students to develop throughout their science and engineering education. Argumentation focuses students on the need for quality evidence, which helps to develop their deep understanding of content [2]. Argumentation has been studied extensively, both in mathematics and science education but also to some extent in engineering education (see for example [3], [4], [5], [6]). After a thorough search of the literature, we found few studies that have considered how teachers support collective argumentation during engineering learning activities.
The purpose of this program of research was to support teachers in viewing argumentation as an important way to promote critical thinking and to provide teachers with tools to implement argumentation in their lessons integrating coding into science, technology, engineering, and mathematics (which we refer to as integrative STEM). We applied a framework developed for secondary mathematics [7] to understand how teachers support collective argumentation in integrative STEM lessons. This framework used Toulmin’s [8] conceptualization of argumentation, which includes three core components of arguments: a claim (or hypothesis) that is based on data (or evidence) accompanied by a warrant (or reasoning) that relates the data to the claim [9], [8]. To adapt the framework, video data were coded using previously established methods for analyzing argumentation [7].
In this paper, we consider how the framework can be applied to an elementary school teacher’s classroom interactions and present examples of how the teacher implements various questioning strategies to facilitate more productive argumentation and deeper student engagement. We aim to understand the nature of the teacher’s support for argumentation—contributions and actions from the teacher that prompt or respond to parts of arguments. In particular, we look at examples of how the teacher supports students to move beyond unstructured tinkering (e.g., trial-and-error) to think logically about coding and develop reasoning for the choices that they make in programming. We also look at the components of arguments that students provide, with and without teacher support. Through the use of the framework, we are able to articulate important aspects of collective argumentation that would otherwise be in the background. The framework gives both eyes to see and language to describe how teachers support collective argumentation in integrative STEM classrooms.
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SAGE-RA: A Reference Architecture to Advance the Teaching and Learning of Computational Thinking
Rapid technological advances and the increasing number of students in Southeast Asian nations present a difficult challenge: how should schools adequately equip teachers with the right tools to effectively teach Computational Thinking, when the demand for such teachers outstrips their readiness and availability? To address this challenge, we present the SAGE reference architecture: an architecture for a learning environment for elementary, middle-school and high-school students based on the Scratch programming language. We synthesize research in the domains of game-based learning, implicit assessments, intelligent tutoring systems, and learning conditions, and suggest a teacher-assisting instructional platform that provides automated and personalized machine learning recommendations to students as they learn Computational Thinking. We discuss the uses and components of this system that collects, categorizes, structures, and refines data generated from students’ and teachers’ interactions, and also facilitates personalized student learning through: 1) predictions of students’ distinct programming behaviors via employment of clustering and classification models, 2) automation of aspects of formative assessment formulations and just-in- time feedback delivery, and 3) utilization of item-based and user-based collaborative filtering to suggest customized learning paths. The proposed reference architecture consists of several architectural components, with explanations on their necessity and interactions to foster future replications or adaptations in similar educational contexts.
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- NSF-PAR ID:
- 10144174
- Date Published:
- Journal Name:
- International Conference on Embedding Artificial Intelligence (AI) in Education Policy and Practice for Southeast Asia
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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