Sharona T. Levy

Examining the Relationship Between Students' Understanding of the Nature of Models and Conceptual Learning in Biology, Physics, and Chemistry

This research addresses high school students’ understandings of the nature of models, and their interaction with model‐based software in three science domains, namely, biology, physics, and chemistry. Data from 736 high school students’ understandings of models were collected using the Students’ Understanding of Models in Science (SUMS) survey as part of a large‐scale, longitudinal study in the context of technology‐based curricular units in each of the three science domains. The results of ANOVA and regression analyses showed that there were differences in students’ pre‐test understandings of models across the three domains, and that higher post‐test scores were associated with having engaged in a greater number of curricular activities, but only in the chemistry domain. The analyses also showed that the relationships between the pre‐test understanding of models subscales scores and post‐test content knowledge varied across domains. Some implications are discussed with regard to how students’ understanding of the nature of models can be promoted.

Making Sense by Building Sense: Kindergarten Children's Construction and Understanding of Adaptive Robot Behaviors

This study explores young children’s ability to construct and explain adaptive behaviors of a behaving artifact, an autonomous mobile robot with sensors. A central component of the behavior construction environment is the RoboGan software that supports children’s construction of spatiotemporal events with an a-temporal rule structure. Six kindergarten children participated in the study, three girls and three boys. Activities and interviews were conducted individually along five sessions that included increasingly complex construction tasks. It was found that all of the children succeeded in constructing most such behaviors, debugging their constructions in a relatively small number of cycles. An adult’s assistance in noticing relevant features of the problem was necessary for the more complex tasks that involved four complementary rules. The spatial scaffolding afforded by the RoboGan interface was well used by the children, as they consistently used partial backtracking strategies to improve their constructions, and employed modular construction strategies in the more complex tasks. The children’s explanations following their construction usually capped at one rule, or two condition-action couples, one rule short of their final constructions. With respect to tasks that involved describing a demonstrated robot’s behavior, in describing their constructions, explanations tended to be more rule-based, complex and mechanistic. These results are discussed with respect to the importance of making such physical/computational environments available to young children, and support of young children’s learning about such intelligent systems and reasoning in developmentally-advanced forms.

Approaching Complexity Through Planful Play: Kindergarten Children’s Strategies in Constructing an Autonomous Robot’s Behavior

This study investigates how young children master, construct and understand intelligent rule-based robot behaviors, focusing on their strategies in gradually meeting the tasks’ complexity. The wider aim is to provide a comprehensive map of the kinds of transitions and learning that take place in constructing simple emergent behaviors, particularly for young children. Six kindergarten children participated individually in the study along five sessions. Regarding modes of engagement, it was found that the children conducted intensive and extended playful investigations of the robot’s behaviors, interacting with it in a variety of ways; it was also found that their constructions were planful and anticipatory, as they could simulate how the behaviors play out even prior to running their programs. Three kinds of transitions were found in the children’s comprehension of the system: one involved adaptation to the formal language; the second, coordination of multiple spatial perspectives; and the third involved a shift from viewing rules as one-time events to their view as recurring and continual descriptions of a process. Finally, it was found that the children employed two strategies to reduce the amount of information in the system: “pruning” involved ignoring part of the logical structure and focusing on another; “fusing” involved coalescing several rules or functions into one. These results are discussed with respect to previous literature on children’s programming and with regards to understanding and supporting young children’s learning through their construction of adaptive autonomous behaviors.

Listening to complexity: blind people’s learning about gas particles through a sonified model

Abstract Students who are blind are usually integrated at public schools with sighted students. Since most of science education curriculum resources are based on visual representations such as diagrams, charts, models (physical and computational), and experimentation in science laboratories, students who are blind lack opportunities for participating and collecting first-hand information. The current research project is based on the assumption that the supply of appropriate information through compensatory sensory channels may contribute to science education performance. In the research system, Listening to Complexity, the user interacts with dynamic objects in a real-time agent-based sonified computer model.

Feeling the forces within materials: bringing inter-molecular bonding to the fore using embodied modelling

ABSTRACT We developed a computerised simulation that utilises embodied modelling by letting students play the role of particles in a liquid. We compared the learning of two eight-grade classrooms that used the embodied modelling simulation during a weeklong learning module on phase change, with a comparison group that used an ordinary simulation with no embodied modelling. In the pre-test, neither group mentioned inter-molecular forces in their explanations. In the post-test, significantly more students from the embodied modelling group mentioned inter-molecular bonds in their explanations than their counterparts who used the regular simulation, and realised that inter-molecular forces influence the motion of particles. However, we found little difference between the groups in students’ ability to relate the magnitude of the inter-molecular forces to the magnitude of the boiling point of the material, showing not only the potential but also the limits in developing complex conceptualisations through this approach. Building on these findings, we discuss the affordances of embodied modelling for learning complex models, and suggest future directions for research into embodied modelling.

Computer-model-based audio and its influence on science learning by people who are blind

ABSTRACT Access to curriculum learning materials is a central need for students who are blind. This research examined the use of Listening-to-Complexity (L2C) based on NetLogo, an agent-based modeling language enabling exploration and construction of models of complex systems. L2C, designed for users who are blind, provides several auditory streams synchronically through sonified feedback. Studied here is a learning curriculum integrating L2C interactions, which covering scientific conceptual knowledge, systems reasoning, and Kinetic Molecular Theory of gas and gas laws in chemistry. The research included ten participants who are blind, using three data collection tools: background questionnaire, pre- and posttest questionnaires, and learning curriculum with the sonified models. Results indicate that the sonified model facilitates access to key challenging scientific concepts, including complex phenomena. Findings indicate gains in learning science content; participants were able to collect and construct scientific knowledge through L2C interactions. There are likely long-term practical benefits in science education for students who are blind, which will facilitate their inclusion in a general K-12 program.

Listen to the models: Sonified learning models for people who are blind

Abstract Students who are blind need access to learning materials. This study looks at the learning of science by people who are blind using a curriculum-based textbook compared to their learning using an identical curriculum integrated with the Listening-to-Complexity (L2C), an agent-based model created on NetLogo. The L2C system employs sonified feedback that provides auditory streams synchronically. This study examines acquisition of scientific conceptual knowledge and systems reasoning for the Kinetic Molecular Theory (KMT) of gas and Gas Laws in chemistry. Twenty persons who are blind participated in this research; they were divided into two experimental groups: those using an accessible curriculum-based textbook and those using the same curriculum integrated with L2C agent-based models. Results showed that all research participants gained scientific knowledge; statistically significant differences were found for both experimental research groups between pre-and posttest. Those who learned through the L2C models performed with higher accuracy in the posttest; furthermore, learning using the NetLogo L2C models predicted their success at the posttest. A comparison of learning task accuracy between the two experimental groups showed that the participants who studied using the NetLogo L2C models performed with statistically significant differences in the five learning activities with integrated L2C models, but no differences were found for the learning activities without integrated L2C models. These research results are likely to have a beneficial impact on integrating sonified models in science education as a compensatory aid, allowing hands-on learning experience for students who are blind. Integrating sonified models will support their inclusion in the K–12 academic curriculum on an equal basis.