The interrelationship between concepts about agency and students' use of teachable-agent learning technology.

To successfully interact with software agents, people must call upon basic concepts about goals and intentionality and strategically deploy these concepts in a range of circumstances where specific entailments may or may not apply. We hypothesize that people who can effectively deploy agency concepts in new situations will be more effective in interactions with software agents. Further, we posit that interacting with a software agent can itself refine a person's deployment of agency concepts. We investigated this reciprocal relationship in one particularly important context: the classroom. In three experiments we examined connections between middle school students' concepts about agency and their success learning from a teachable-agent-based computer system called "Betty's Brain". We found that the students who made more intentional behavioral predictions about humans learned more effectively from the system. We also found that students who used the Betty's Brain system distinguished human behavior from machine behavior more strongly than students who did not. We conclude that the ability to effectively deploy agency concepts both supports, and is refined by, interactions with software agents.

Identifying middle school students' challenges in computational thinking-based science learning.

Computational thinking (CT) parallels the core practices of science, technology, engineering, and mathematics (STEM) education and is believed to effectively support students' learning of science and math concepts. However, despite the synergies between CT and STEM education, integrating the two to support synergistic learning remains an important challenge. Relatively, little is known about how a student's conceptual understanding develops in such learning environments and the difficulties they face when learning with such integrated curricula. In this paper, we present a research study with CTSiM (Computational Thinking in Simulation and Modeling)-computational thinking-based learning environment for K-12 science, where students build and simulate computational models to study and gain an understanding of science processes. We investigate a set of core challenges (both computational and science domain related) that middle school students face when working with CTSiM, how these challenges evolve across different modeling activities, and the kinds of support provided by human observers that help students overcome these challenges. We identify four broad categories and 14 subcategories of challenges and show that the human-provided scaffolds help reduce the number of challenges students face over time. Finally, we discuss our plans to modify the CTSiM interfaces and embed scaffolding tools into CTSiM to help students overcome their various programming, modeling, and science-related challenges and thus gain a deeper understanding of the science concepts.