Using Stratified Attribute Tracking (SAT) Diagrams for Learning Analytics

Majumdar, Rwitajit; Iyer, Sridhar

doi:10.1109/icalt.2014.115

Cited by 7 publications

(4 citation statements)

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“…Then we explicated the pattern between the difficulty level and the stratified (low, medium, high) scores of the fourth week quiz using stratified attribute tracking diagrams (Majumdar and Iyer 2014). …”

Section: Problem Posing As An Assessment Toolmentioning

confidence: 99%

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An exploration of problem posing-based activities as an assessment tool and as an instructional strategy

Mishra

Iyer

2015

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BackgroundProblem posing, the generation of questions by learners, has been shown to be an effective instructional strategy for teaching–learning of complex materials in domains such as mathematics. In this paper, we demonstrate the potential of problem posing in two dimensions. Firstly, we present how problem posing can result in unfolding of knowledge and hence how it can be used as an instructional strategy. Then we present another problem posing-based activity as an assessment tool in an Introductory Programming course (CS1).MethodTo explore the potential of problem posing as an instructional strategy, we conducted field studies in the two CS application courses (Data Structures (DS) and Artificial Intelligence (AI)), in which we provided a semi-structured problem posing situation to students. We performed inductive qualitative research and development the questions generated by students using grounded theory-based qualitative data analysis technique. To explore the potential of problem posing as an assessment tool, we conducted a field study in CS1 wherein we employed another problem posing (PP)-based activity in a large class for assessing the learning of computational thinking concepts in an introductory programming course and analysed how performance in traditional assessment tools (quiz score) is related with performance in our non-traditional assessment tool (quality of problems posed during a problem posing activity).ResultsFrom the studies in DS and AI courses we found that students pose questions and unfold knowledge using seven strategies — Apply, Organize, Probe, Compare, Connect, Vary, and Implement. From the field study performed in the CS1 course we found that the quality of the problems posed (difficulty level) were mostly aligned to the traditional assessment results in the case of novice learners but not in the case of advanced learners.

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Section: Problem Posing As An Assessment Toolmentioning

confidence: 99%

“…To answer RQ2, we operationalized the quality of questions using difficulty levels of the questions. Then we explicated the pattern between the difficulty level and the stratified (low, medium, high) scores of the fourth week quiz using stratified attribute tracking diagrams (Majumdar and Iyer 2014).…”

Section: Problem Posing As An Assessment Toolmentioning

confidence: 99%

An exploration of problem posing-based activities as an assessment tool and as an instructional strategy

Mishra

Iyer

2015

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“…Earlier studies on iSAT have demonstrated its development process over three research-based design iterations (Majumdar et al 2014) and its potential to be used for learning analytics (Majumdar and Iyer 2014). In this paper, we describe the utility of iSAT for instructors.…”

Section: Resultsmentioning

confidence: 99%

“…Warriem et al (2013) tracked online learners’ performance in participation for completing and submission of assessment. Majumdar and Iyer (2014) studied consistency of survey responses across different questions asked to understand student’s perception, using iSAT. Readers who are interested in details of evolution of iSAT across its design iteration can refer to Majumdar et al (2014).…”

Section: More Uses Of Isat For Instructorsmentioning

confidence: 99%

iSAT: a visual learning analytics tool for instructors

Majumdar

Iyer

2016

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Interactive Stratified Attribute Tracking (iSAT) is a visual analytics tool for cohort analysis. In this paper, we show how instructors can use iSAT to visualize transitions of groups of students during teaching-learning activities. Interactive visual analytics gives the instructor the affordance of understanding the dynamics of the class of students and their activities from the data collected in their own teaching-learning context. We take an example of a peer instruction (PI) activity and describe how iSAT can be used to analyze its clicker responses. During PI, typically instructors only use histograms to visualize the distribution of clicker responses in the pre-and postdiscussion phases. We show that the use of iSAT to analyze clicker data in real time to trace transitions of participants' responses during various voting phases can support them in planning for their post-PI activities. Seven patterns of transitions that emerge are aligned, returns, starburst, slide, attractor, switching, and void. We interpret them in the context of the example. Such transition patterns are neither available in multiple histograms of individual voting phase nor generated in real time to be visualized as a flow diagram. We had conducted two workshops to introduce iSAT to the instructors and demonstrated the workflow of using iSAT with their dataset. Here, we report usefulness and usability data collected from those workshops. In conclusion, we highlight the power of iSAT for instructors to do cohort analysis in their teaching-learning practice.

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