7 research outputs found
The effect of reading to find a solution on learning from multiple documents in science
Advisors: M. Anne Britt.Committee members: Amanda Durik; Keith Millis; Jennifer Wiley.Includes bibliographical references.Includes illustrations.Reading for understanding in science is a complex process that requires the integration of information across many sources. This can be a very challenging task as many readers may not be familiar with how to read scientific texts or may simply not be interested in doing so. The present study aims to determine whether or not giving readers prompts asking them to find a solution to the problem of global climate change will help them better comprehend the causal information in a document set. Additionally, if solution reading prompts do have an effect on comprehension, the present study aims to examine if that effect is due to the prompt changing the readers' goals while reading or due to increasing their interest in the task. The results of the study showed no significant difference in deep comprehension of causal information due to reading prompts. However, readers who received a reading prompt focused on finding solutions to climate change had poorer comprehension of surface level information than those without a solution focused prompt. Due to the lack of direct effects of prompt on deep comprehension, the mediating effects of reader goals and interest could not be examined.M.A. (Master of Arts
A Reasoned Approach to Dealing With Fake News
International audienceWe now have almost no filters on information that we can access, and this requires a much more vigilant, knowledgeable reader. Learning false information from the web can have dire consequences for personal, social, and personal decision making. Given how our memory works and our biases in selecting and interpreting information, now more than ever we must control our own cognitive and affective processing. As examples: Simply repeating information can increase confidence in its perceived truth; initial incorrect information remains available and can continue to have an effect despite learning the corrected information; and we are more likely to accept information that is consistent with our beliefs. Information evaluation requires readers (a) to set and monitor their goals of accuracy, coherence, and completeness; (b) to employ strategies to achieve these goals; and (c) to value this time- and effort-consuming systematic evaluation. Several recommendations support a reasoned approach to fake news and manipulation
Assessing Water Literacy: Undergraduate Student Conceptions of Groundwater and Surface Water Flow
Given the importance of fresh water, we investigated undergraduate students’ understanding of water flow and its consequences. We probed introductory geology students’ pre-instruction knowledge using a classroom management system at two large research-intensive universities. Open-ended clicker questions, where students click directly on diagrams using their smart device (e.g., cell phone, tablet) to respond, probed students’ predictions about: (1) groundwater movement and (2) velocity and erosion in a river channel. Approximately one-third of students correctly identified groundwater flow as having lateral and vertical components; however, the same number of students identified only vertical components to flow despite the diagram depicting enough topographic gradient for lateral flow. For rivers depicted as having a straight channel, students correctly identified zones of high velocity. However, for curved river channels, students incorrectly identified the inside of the bend as the location of greatest erosion and highest velocity. Systematic errors suggest that students have mental models of water flow that are not consistent with fluid dynamics. The use of students’ open-ended clicks to reveal common errors provided an efficient tool to identify conceptual challenges associated with the complex spatial and temporal processes that govern water movement in the Earth system
Assessing Water Literacy: Undergraduate Student Conceptions of Groundwater and Surface Water Flow
Given the importance of fresh water, we investigated undergraduate students’ understanding of water flow and its consequences. We probed introductory geology students’ pre-instruction knowledge using a classroom management system at two large research-intensive universities. Open-ended clicker questions, where students click directly on diagrams using their smart device (e.g., cell phone, tablet) to respond, probed students’ predictions about: (1) groundwater movement and (2) velocity and erosion in a river channel. Approximately one-third of students correctly identified groundwater flow as having lateral and vertical components; however, the same number of students identified only vertical components to flow despite the diagram depicting enough topographic gradient for lateral flow. For rivers depicted as having a straight channel, students correctly identified zones of high velocity. However, for curved river channels, students incorrectly identified the inside of the bend as the location of greatest erosion and highest velocity. Systematic errors suggest that students have mental models of water flow that are not consistent with fluid dynamics. The use of students’ open-ended clicks to reveal common errors provided an efficient tool to identify conceptual challenges associated with the complex spatial and temporal processes that govern water movement in the Earth system
Different Approaches to Assessing the Quality of Explanations Following a Multiple-Document Inquiry Activity in Science
This article describes several approaches to assessing student understanding using written explanations that students generate as part of a multiple-document inquiry activity on a scientific topic (global warming). The current work attempts to capture the causal structure of student explanations as a way to detect the quality of the students’ mental models and understanding of the topic by combining approaches from Cognitive Science and Artificial Intelligence, and applying them to Education. First, several attributes of the explanations are explored by hand coding and leveraging existing technologies (LSA and Coh-Metrix). Then, we describe an approach for inferring the quality of the explanations using a novel, two-phase machine-learning approach for detecting causal relations and the causal chains that are present within student essays. The results demonstrate the benefits of using a machine-learning approach for detecting content, but also highlight the promise of hybrid methods that combine ML, LSA and Coh-Metrix approaches for detecting student understanding. Opportunities to use automated approaches as part of Intelligent Tutoring Systems that provide feedback toward improving student explanations and understanding are discussed
Explanatory Modeling in Science Through Text-Based Investigation: Testing the Efficacy of the Project READI Intervention Approach
This article reports the results of a randomized control trial of a semester-long intervention designed to promote ninth-grade science students’ use of text-based investigation to create explanatory models of biological phenomena. The main research question was whether the student participants in the intervention outperformed the students in the control classes, as assessed by several measures of comprehension and application of information to modeling biological phenomena not covered in the instruction. A second research question examined the impact on the instructional practices of the teachers who implemented the intervention. Multilevel modeling of outcome measures, controlling for preexisting differences at individual and school levels, indicated significant effects on the intervention students and teachers relative to the controls. Implications for classroom instruction and teacher professional development are discussed