Inq-ITS: Creating rigorous assessment and real-time support of science learning: Creating rigorous assessment and real-time support of science learning

摘要

This article is an example of how theoretical frameworks about how people learn science were used in combination with computational techniques to develop authentic assessments and intelligent tutoring for science. In spite of the billions of dollars spent on education every year in the U.S., American students continue to score much lower on science compared to students from other developed countries. In 2018, for example, American students ranked 18th on science in the Programme for International Student Assessment (PISA). One of the main reasons cited for this is the American public school system was modeled on a "one-size fits all" approach that cannot address students' individual differences known to be critical to science learning including (but not limited to) prior knowledge, competencies (or skills) for "doing" science, language proficiency for reading and communicating about science, and motivation or engagement for science.