This pre-master's course in quantitative methods runs for four weeks, and is a pre-enrolment course taken by a total of 15 groups of between 25-50 students over the year. The course was designed and delivered by Marit Spek and Dr. Tim de Leeuw at TIAS School for Business and Society. The strategy of the school called for a sustainable integration of online and blended education, with several master's courses being redesigned.
As a result of these changes, instructors sought a way to gain oversight on student performance and to be able to differentiate. For these reasons, the Interactive Document tool was integrated into the course within Canvas, both enriching assignments with more interactivity, and receiving detailed analytics on learner progress.
Students are able to understand, apply and evaluate basic quantitative concepts and techniques, understand and visualise quantitative data, explain relationships between variables, conduct analyses, and critically evaluate (mis-)use of statistics.
Step 1: Assignment submission
Students hand in weekly assignments about statistical analyses in SPSS, each containing 10 related questions and problems
Step 2: Interactive Document activity
Students accessed the document with the solutions, and self-corrected the correctness of their own answers, compared to those found in the detailed step-by-step answers.
Self-reporting took the form of answering a multiple choice question for each problem according to a 3-point scale (correct, partially correct, or incorrect).
Step 3: Synchronous lessons
Instructor addressed the most common problems in the homework assignments based on the student analytics from Interactive Document.
Students who answered everything correctly for the first 5 questions were not required to be available for the part of the lesson where explanations on these questions were given and could use the time to work on the next assignment. On the other hand, where more students reported problems with a particular question, the instructor was able to devote more time to addressing this in class.
The use of Interactive Document
Interactive Document is commonly used to guide students through a text with in-line questions, comments and didscussions. In this course however, it was used to save the teacher time and support student self-regulation by creating learning analytics detailing how students evaluated their own answers to an assignment.
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FeedbackFruits tools were used only for formative assessment, providing insights into the self assessments of all students both individually as well as collectively. The summative portion of this course took the form of an online exam consisting of 100% of the grade.
Time-saving in analysing and processing student performance: The downloaded student analytic data was found to be useful to assess students' uptake of material.
Timely adjustment and intervention: Data gathered from students self-evaluations allowed the instructor to carry out a tailored approach to lessons, where the pertinent questions would be addressed.
Students' autonomy over their learning process was increased as they were given more opportunity to self-report their encounter with materials, as well as identify and address areas where more feedback or attention was required. This in turn had a positive effect on their motivation and engagement.
“Students get more autonomy over their learning, and teaching is made as effective as possible.” – Marit Spek, Instructional Designer at TIAS School for Business and Society
An announcement with a video introduction and course expectations is made within the LMS so that students know where and when assignments will become available.
The instructor is able to gauge student performance, self-reporting of skills and knowledge, and progress with the assignment within the Interactive Study Materials interface.
At the end of the course data is downloaded in a compiled excel spreadsheet for further analysis.
Integrated into Canvas, Interactive Study Materials provides comprehensive insights into student performance at individual, group, and class-wide levels. This data allows for scalable analysis and the differentiation of course material according to varying student needs.
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