|Title:||Developing Guidelines for Optimizing Levels of Students' Overt Engagement Activities|
|Principal Investigator:||Chi, Michelene||Awardee:||Arizona State University|
|Program:||Cognition and Student Learning [Program Details]|
|Award Period:||2011–2014||Award Amount:||$1,399,212|
|Type:||Development and Innovation||Award Number:||R305A110090|
Co-Principal Investigators: Roy Levy
Purpose: "Active learning" is often defined as engaging students in more meaningful learning. A variety of concrete activities are offered in the literature for ways that students can be more cognitively engaged while learning in a variety of instructional contexts, such as asking questions and taking notes. However, there are no criteria for determining what constitutes a cognitively engaging activity. Also, there are no recommendations for which student activities are more engaging than others nor concrete guidelines for teachers to know how they can improve their routine activities so students become more engaged. To address these needs, the research team will develop guidelines that specify how teachers can modify student activities to optimize their engagement, provide this information to teachers in the form of a short web-based module, and evaluate student learning outcomes associated with teachers' improvement of students' activities.
Project Activities: Using an iterative design, the research team will collaborate with teachers to create a web-based module for teacher use. This module will help teachers think about and use theories of active learning as a way to improve instruction. During the development process, teachers will use the module to refine their lessons and test them in their classrooms. Based on teacher feedback and student performance, the research team will improve the module.
Products: The main product from this work will be an online module intended for teachers that will explain levels of student engagement. This module will include information related to student behavior, , provide characteristics of overt activities for each level of engagement, and give examples of concrete practical procedures that teachers can use to modify and improve their regular classroom and homework learning activities. The researchers will also publish scholarly reports of findings describing the association between use of the module and student outcomes.
Setting: The study will take place in an urban middle/junior high, high schools, and community college classrooms in Arizona.
Population: One set of participants will be 6th through 12th grade charter school students. Pilot study participants will be 7th–8th grade students from two public schools. One school has an ethnically diverse population, with over 88% minority students and low socioeconomic status, and the other school has a less diverse population, with approximately 20% minority students.
Intervention: The main component of the intervention is a professional development module that explains and demonstrates various active learning behaviors to teachers. This module will describe the characteristics of overt activities associated with each level of engagement and give teachers examples of recommended practical procedures that can be adopted to enrich their classroom and homework activities.
Research Design and Methods: To build this module, the research team has already differentiated and classified students' overt activities into four levels of engagement: passive, active, constructive, and interactive. The research team will collaborate with teachers to develop and refine an online module that explains the different levels of student engagement to teachers, with a focus on overt behavior. Four iterations of the module will be evaluated in different academic settings and student populations. In each iteration, after teachers complete the module, they will improve a learning activity of their choice and use it in some of their classrooms.
Control Condition: In evaluating different iterations of the module, the teachers will designate one out of every two sections of the same class as the control group. The teacher will assign "non-improved" learning activities to the control group.
Key Measures: Students' test scores, their generated work sheets, and in-class observations of teachers and students will be collected and assessed to evaluate the effectiveness of the modified activities. Exam questions already in existence will be selected for pre- and post-tests. Questions to evaluate deep learning that focus on understanding and synthesis of information, may be added as needed. Products from students' activities will also be collected and scored, to validate that they are undertaking the assigned activities.
Data Analytic Strategy: Scores on multiple-choice pre- and post-tests for different content will be standardized to place scores on a common, comparable metric. Multilevel models will be used for investigation of the effects of level of engagement in aggregate, pooling across variability due to differences between teachers and content areas. Multilevel modeling will also allow investigation of whether the effects of level of engagement vary by teacher or by content area. Qualitative data, such as observations of student behavior during learning activities and written products of learning activities, will also be coded and analyzed using developed guidelines.
Chi, M. T. H., & Menekse, M. (2015). Dialogue Patterns in Peer Collaboration That Promote Learning. Socializing Intelligence Through Academic Talk and Dialogue . American Educational Research Association.
Journal article, monograph, or newsletter
Chi, M.T.H., and VanLehn, K.A. (2012). Seeing Deep Structure From the Interactions of Surface Features. Educational Psychologist, 47(3): 177–188.
Chi, M.T.H., and Wylie, R. (2014). The ICAP Framework: Linking Cognitive Engagement to Active Learning Outcomes. Educational Psychologist, 49(4): 219–243.
Menekse, M., Stump, G. S., Krause, S., & Chi, M. T. H. (2013). Differentiated Overt Learning Activities for Effective Instruction in Engineering Classrooms. Journal of Engineering Education, 102(3): 346–374.