{"content":[{"text":"a “cross-over” study where each group experiences the same intervention but at \n different points in time: e.g., Group A experiences the intervention before the midterm, \n and then Group B gets it after the midterm. In any experimental design, you need to \n identify the elements in the environment that possibly confound the effect of the \n intervention and try your best to minimize their influence or control for their effects using \n statistical methods.","bbox":{"left":0.117686,"top":0.088889,"width":0.7599880000000001,"height":0.10793900000000001}},{"text":"You can also consider establishing “process causality” (Anderson & Scott, 2012) by \n identifying the “generative mechanisms” that can explain how the changes took place, \n which can include individuals’ belief, reasoning and action in response to the \n intervention. You can do this by asking your research participants to explain how the \n intervention made a difference to the outcome of interest (e.g., student learning) via \n open-ended survey questions, interviews or focus groups. Then you can analyze the \n qualitative data by using methods such as causation or pattern coding (Saldaña, 2016). \n When you include this component in your pre-test/post-test quantitative design, you \n have conducted a mixed-methods study.","bbox":{"left":0.117686,"top":0.21343,"width":0.756654,"height":0.15767799999999998}},{"text":"There are some good references for designing an intervention study (Harackiewicz & \n Priniski, 2018). An intervention study starts with identifying and assessing the specific \n problem, population and context targeted by an intervention. You also need to consider \n what measurement you will use to assess particular academic outcomes, which serve \n as a measure of intervention efficacy. These outcomes can be course-specific (e.g., \n motivation for taking a course), school-specific (e.g., graduation rate) or field-specific \n (e.g., retention rate of female engineering students), depending on the scope of the \n intervention. The outcomes can be cognitive (e.g., development of problem-solving \n skills) or affective (e.g., self-efficacy). Some outcomes can be demonstrated shortly \n after the intervention and others may be more appropriate for a longer-term. So, you \n also need to decide when to measure the outcomes.","bbox":{"left":0.117686,"top":0.385139,"width":0.7539610000000001,"height":0.19508599999999998}},{"text":"A study design that follows these principles can provide a substantially enhanced level \n of quality to your research, and your papers, because it uses a rigorous research \n process to assess your intervention.","bbox":{"left":0.117686,"top":0.594255,"width":0.747356,"height":0.05566700000000002}},{"text":"Anderson, G. L., & Scott, J. (2012). Toward an intersectional understanding of process causality and social context. \n Qualitative Inquiry, 18(8), 674-685. \n Gravetter, F., & Wallnau, L. B. (2013). Statistics for the behavioral sciences (9th ed.). Belmont, CA: \n Wadsworth, Cengage Learning. \n Harackiewicz, J.M., & Priniski, S.J. (2018). Improving student outcomes in higher education: The science \n of targeted intervention. Annual Review of Psychology, 69(1), 409-435. \n Saldaña, J. (2016). The coding manual for qualitative researchers. Los Angeles, CA: SAGE publications. \n Turoski, S.A., & Schell, W. J. (2020, June). Advancing student motivation and course interest through a \n utility value intervention in an engineering design context. Paper in the proceedings of the annual \n Canadian Engineering Education Association conference.","bbox":{"left":0.117686,"top":0.665448,"width":0.7563240000000001,"height":0.14631700000000003}},{"text":"Authors: Qin Liu and Susan McCahan, University of Toronto","bbox":{"left":0.117686,"top":0.826187,"width":0.5609350000000001,"height":0.020863999999999994}},{"text":"Except where otherwise noted, this guide document is licensed under a Creative \n Commons Attribution-ShareAlike 4.0 International License. \n Distributed: May 17, 2021","bbox":{"left":0.117686,"top":0.861362,"width":0.580436,"height":0.0463070000000001}}],"images_bbox":[{"left":0.771078,"top":0.863003,"width":0.111275,"height":0.030303}],"images_bbox_not_text_overlap":[{"left":0.771078,"top":0.863003,"width":0.111275,"height":0.030303}]}