Nirmal Patel

• Chief Data Scientist at Playpower Labs

Generative AI systems are increasingly capable of expressing emotions via text and imagery. Effective emotional expression will likely play a major role in the efficacy of AI systems -- particularly those designed to support human mental health and wellbeing. This motivates our present research to better understand the alignment of AI expressed emo...

In this study, we analyze data from the National Assessment of Education Progress (NAEP) digital test to understand how digital tool usage relates to the efficiency of answering questions. Digital testing software provides students with on-screen tools such as calculators and scratchpads. We found that students who used digital tools in NAEP were s...

[ Background ] Readability metrics provide us with an objective and efficient way to assess the quality of educational texts. We can use the readability measures for finding assessment items that are difficult to read for a given grade level. Hard‐to‐read math word problems can put some students at a disadvantage if they are behind in their litera...

Intelligent Tutoring Systems (ITS) can only respond adaptively to the digital learning activities of the students. If students are learning offline without any digital devices, they have little or no means to receive personalized learning materials with the help of intelligent systems. This paper proposes a Paper-Digital Integration System that can...

Technology aided learning is becoming increasingly popular. In some of the countries, online learning has taken over for traditional classroom-based learning. With this, educational data is being generated in vast amounts. Knowing the potential of this data, many education stakeholders have turned to evidence-based decision making to improve the le...

Process Analysis is an emerging approach to discover meaningful knowledge from temporal educational data. The study presented in this paper shows how we used Process Analysis methods on the National Assessment of Educational Progress (NAEP) test data for modeling and predicting student test-taking behavior. Our process-oriented data exploration gav...

In this paper, we describe our Knowledge Tracing model for the 2020 NeurIPS Education Challenge. We used a combination of 22 models to predict whether the students will answer a given question correctly or not. Our combination of different approaches allowed us to get an accuracy higher than any of the individual models, and the variation of our mo...

Showing progress towards a goal is a well-established motivational design tactic. This paper describes how university students designed a new "progress meter" for an online learning game and then evaluated the effects of the design using a controlled online experiment, or A/B test. Using the UpGrade A/B testing platform, we randomly assigned 3,200...

UpGrade is an open-source tool for A/B testing in educational software. We this study, we used UpGrade to run large scale online experiments in an educational game. Our experiments were aimed at increasing the student engagement. We experimented with various features of the game such as question difficulty, game narrative, feedback style, etc. to f...

This paper describes a new, open source tool for A/B testing in educational software called UpGrade. We motivate UpGrade's approach, describe development goals and UpGrade's software architecture, and provide a brief overview of working within UpGrade to define and monitor experiments. We conclude with some avenues for future research and developme...

We propose to build a Curriculum Pacing workflow component in the LearnSphere environment. Curriculum Pacing is a way to visualize student learning trajectories through curriculum data. It is a visual learning analytic method that allows its users to observe how students interacted with curriculum topics over time, which modules of the curriculum w...

The primary goal of this workshop is to produce open source data visualizations that help communicate results of learning analytics (LA) research to educators. Instructors are increasing their use of data to drive instruction, and various results of LA research are useful towards this end. However, the actionable insights discovered by the LA commu...

In this paper, we present a novel data visualization that shows the distribution of Cronbach's Alpha for a large number of assessments and their items. Cronbach's alpha measure can be used to improve assessments by removing items that are not consistent with other items of the test. Exclusion of items can affect alpha of the assessment in a differe...

This paper examines the use of “pacing plots” to represent variations in student learning sequences within a digital curriculum. Pacing plots are an intuitive and flexible data visualizations that have a potential for revealing the diversity of blended classroom instructional models. By using curriculum pacing plots, we identified several common im...

Neuropsychological assessments are used to measure and characterize cognitive function. However, in-lab assessments are expensive and inconvenient to administer. This paper describes a series of game-based mobile cognitive assessments designed to measure cognitive functions such as inhibition, processing speed, working memory and reasoning skills....

In this paper, we describe data mining techniques used to extract frequent learning pathways from a large educational dataset. These pathways were extracted as a directed graph that encoded student learning processes. Our dataset contains more than 800 million interactions of over 3 million anonymized students in an online learning platform. Perfor...

Many game designers aim to optimize difficulty to make games that are "not too hard, not too easy." However, recent experiments have shown that even moderate difficulty can reduce player engagement. The present work investigates other design factors that may account for the purported benefits of difficulty, such as choice, novelty and suspense. The...

"Multi-armed bandits" offer a new paradigm for the AI-assisted design of user interfaces. To help designers understand the potential, we present the results of two experimental comparisons between bandit algorithms and random assignment. Our studies are intended to show designers how bandits algorithms are able to rapidly explore an experimental de...