There have been multiple calls to incorporate the teaching of scientific practices within science laboratory courses over the past decade. To accomplish this goal, changes must be made to the curriculum standards, instructional programs, and assessment-evaluation systems used in laboratory courses. One instructional program that can used in a laboratory course to help students learn scientific practices such as investigation design, collecting and analyzing data, argument generation and critique, and science writing is the argument-driven inquiry (ADI) instructional model. This article describes the development of an end-of-course assessment, the Investigation Design, Explanation, and Argument Assessment for General Chemistry I Laboratory (IDEAA-GC1), that educators can use to measure students' ability to use scientific practices after incorporating the ADI instructional model into the General Chemistry I Laboratory. This new instrument has strong face and content validity as well as consistent instructor grading. The face validity of the instrument was established through iterative revisions of the IDEAA-GC1 based on faculty and student feedback. Content validity was established through the alignment of the IDEAA-GC1 with scientific practices and anchoring concepts as described by the Three-Dimensional Learning Assessment Protocol and the General Chemistry Anchoring Concepts Content Map.

When implementing innovative teaching techniques, instructors often seek to gauge the success of their methods. Proposing one approach to assessing classroom innovation, this study examines the ability of students' ratings of engagement and instructional practices to predict their learning in a cooperative (team-based) framework. After identifying the factor structures underlying measures of student engagement and instructional practices, these factors were used as predictors of self-reported student learning in a general chemistry course delivered using a team-based learning approach. Exploratory factor analyses showed a fourfactor structure of engagement: teamwork involvement, investment in the learning process, feelings about team-based learning, level of academic challenge; and a three-factor structure of instructional practices: instructional guidance, fostering self-directed learning skills, and cognitive level. Multiple linear regression revealed that feelings about team-based learning and perceptions of instructional guidance had significant effects on learning, beyond other predictors, while controlling gender, GPA, class level, number of credit hours, whether students began college at their current institution, expected highest level of education, racial or ethnic identification, and parental level of education. These results yield insight into student perceptions about team-based learning, and how to measure learning in a team-based learning framework, with implications for how to evaluate innovative instructional methods.

When implementing innovative teaching techniques, instructors often seek to gauge the success of their methods. Proposing one approach to assessing classroom innovation, this study examines the ability of students' ratings of engagement and instructional practices to predict their learning in a cooperative (team-based) framework. After identifying the factor structures underlying measures of student engagement and instructional practices, these factors were used as predictors of self-reported student learning in a general chemistry course delivered using a team-based learning approach. Exploratory factor analyses showed a fourfactor structure of engagement: teamwork involvement, investment in the learning process, feelings about team-based learning, level of academic challenge; and a three-factor structure of instructional practices: instructional guidance, fostering self-directed learning skills, and cognitive level. Multiple linear regression revealed that feelings about team-based learning and perceptions of instructional guidance had significant effects on learning, beyond other predictors, while controlling gender, GPA, class level, number of credit hours, whether students began college at their current institution, expected highest level of education, racial or ethnic identification, and parental level of education. These results yield insight into student perceptions about team-based learning, and how to measure learning in a team-based learning framework, with implications for how to evaluate innovative instructional methods. KEYWORDS student engagement, student learning, team-based learning, general chemistry, predictors of learning outcomes Student engagement has been regarded as a determining factor for promoting academic achievement (