Assessment

In successful peer discussions students respond to each other and benefit from supports that focus discussion on one another’s ideas. We explore using artificial intelligence (AI) to form groups and guide peer discussion for grade 7 students. We use natural language processing (NLP) to identify student ideas in science explanations. The identified ideas, along with Knowledge Integration (KI) pedagogy, informed the design of a question bank to support students during the discussion. We compare groups formed by maximizing the variety of ideas among participants to randomly formed groups.

In successful peer discussions students respond to each other and benefit from supports that focus discussion on one another’s ideas. We explore using artificial intelligence (AI) to form groups and guide peer discussion for grade 7 students. We use natural language processing (NLP) to identify student ideas in science explanations. The identified ideas, along with Knowledge Integration (KI) pedagogy, informed the design of a question bank to support students during the discussion. We compare groups formed by maximizing the variety of ideas among participants to randomly formed groups.

With the widespread adoption of the Next Generation Science Standards (NGSS), science teachers and online learning environments face the challenge of evaluating students’ integration of different dimensions of science learning. Recent advances in representation learning in natural language processing have proven effective across many natural language processing tasks, but a rigorous evaluation of the relative merits of these methods for scoring complex constructed response formative assessments has not previously been carried out.

With the widespread adoption of the Next Generation Science Standards (NGSS), science teachers and online learning environments face the challenge of evaluating students’ integration of different dimensions of science learning. Recent advances in representation learning in natural language processing have proven effective across many natural language processing tasks, but a rigorous evaluation of the relative merits of these methods for scoring complex constructed response formative assessments has not previously been carried out.

The purpose of this study was to explore the problem-solving behaviors of middle-school students with learning disabilities (SLD). Think-aloud interviews were performed with 20 seventh- and eighth-grade students who had learning disabilities to observe their behaviors while solving mathematical word problems (i.e., behaviors and patterns of behaviors). Themes emerged from qualitative analysis indicating that the students engaged in problem-solving behaviors, as well as common patterns of behaviors.

The purpose of this study was to explore the problem-solving behaviors of middle-school students with learning disabilities (SLD). Think-aloud interviews were performed with 20 seventh- and eighth-grade students who had learning disabilities to observe their behaviors while solving mathematical word problems (i.e., behaviors and patterns of behaviors). Themes emerged from qualitative analysis indicating that the students engaged in problem-solving behaviors, as well as common patterns of behaviors.

The purpose of this study was to explore the problem-solving behaviors of middle-school students with learning disabilities (SLD). Think-aloud interviews were performed with 20 seventh- and eighth-grade students who had learning disabilities to observe their behaviors while solving mathematical word problems (i.e., behaviors and patterns of behaviors). Themes emerged from qualitative analysis indicating that the students engaged in problem-solving behaviors, as well as common patterns of behaviors.

The purpose of this study was to explore the problem-solving behaviors of middle-school students with learning disabilities (SLD). Think-aloud interviews were performed with 20 seventh- and eighth-grade students who had learning disabilities to observe their behaviors while solving mathematical word problems (i.e., behaviors and patterns of behaviors). Themes emerged from qualitative analysis indicating that the students engaged in problem-solving behaviors, as well as common patterns of behaviors.

To better understand integrated STEM education, this work explored scores on the STEM Observation Protocol (STEM-OP), a newly developed observation protocol for use in K-12 science and engineering classrooms. The goals of this work were to better understand how integrated STEM might look throughout an integrated STEM unit and identify limitations of the instrument when examining daily scores and full unit implementation scores. The work takes a mixed methods approach to first examine what scores may be typically seen with daily and unit implementations.

To better understand integrated STEM education, this work explored scores on the STEM Observation Protocol (STEM-OP), a newly developed observation protocol for use in K-12 science and engineering classrooms. The goals of this work were to better understand how integrated STEM might look throughout an integrated STEM unit and identify limitations of the instrument when examining daily scores and full unit implementation scores. The work takes a mixed methods approach to first examine what scores may be typically seen with daily and unit implementations.