Dimension Objective Learning Evaluation activity/ies Knowledge Read textbook and primary Online lectures, Self-testing source meetings; class online and mastery powerpoints and transcripts. demonstrations, learning; Identify the major topics covered weekly TA review each week and the relationship to sessions, readings choice the course roadmap examination Reproduce simple analysis and data strategies demonstrated in lecture Comprehension Define the major concepts/terms Online Self-testing each week demonstrations , and mastery the appropriate discussion learning, Describe situations in which to use weekly TA review practice techniques demonstrated sessions, readings exercises, Differentiate among different approaches (e.g., different kinds choice of transformations or analysis examination strategies) and their strengths and weaknesses Application major coefficients and Online Self-testing Calculate summary statistics demonstrations , and mastery Chart key findings and interpret Hands-on class learning; Choose the best sessions, practice analysis/transformation for a given based problem exercises, situation solving, weekly TA data analysis Extend basic analysis situations review sessions homework demonstrated in class to more (output complex data problems generation) Analysis Break down the multiple results Team-based Peer-review of a data analysis into constituent problem solving, and group pieces discussion, Examine variable distributions coaching/mentoring evaluation, and determine if conformal for data analysis analysis homework the results of analyses (analysis Interpret with regards to the substantive selection and questions being asked output Recommend next steps or areas interpretation) in need of clarification to improve the analysis Synthesis Collaborate with group members Coaching/mentoring, Multiple to determine the best solution to a Team-based complex problem problem solving examination Combine multiple sources of (questions information (e.g., information combining regarding distributions and multiple analytical question) aspects of
Dimension Objective Learning activity/ies Evaluation Knowledge Read textbook and primary source meetings; class powerpoints and transcripts. Identify the major topics covered each week and the relationship to the course roadmap Reproduce simple analysis and data strategies demonstrated in lecture Online lectures, online demonstrations, weekly TA review sessions, readings Self-testing and mastery learning; examination Comprehension Define the major concepts/terms each week Describe the appropriate situations in which to use techniques demonstrated Differentiate among different approaches (e.g., different kinds of transformations or analysis strategies) and their strengths and weaknesses Online demonstrations , discussion weekly TA review sessions, readings Self-testing and mastery learning, practice exercises, examination Application Calculate major coefficients and summary statistics Chart key findings and interpret Choose the best analysis/transformation for a given situation Extend basic analysis situations demonstrated in class to more complex data problems Online demonstrations , Hands-on class sessions, problem solving, weekly TA review sessions Self-testing and mastery learning; practice exercises, data analysis homework (output generation) Analysis Break down the multiple results of a data analysis into constituent pieces Examine variable distributions and determine if conformal for analysis Interpret the results of analyses with regards to the substantive questions being asked Recommend next steps or areas in need of clarification to improve the analysis Team-based problem solving, discussion, coaching/mentoring Peer-review and group data analysis homework (analysis selection and output interpretation) Synthesis Collaborate with group members to determine the best solution to a complex problem Combine multiple sources of information (e.g., information regarding distributions and analytical question) Coaching/mentoring, Team-based problem solving Multiple choice examination (questions combining multiple aspects of choice evaluation, based
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