Shitanshu Mishra, PhD
National Information Technology Officer, UNESCO MGIEP (2022 - Current)
Information Technology Officer, UNESCO MGIEP (2021 - 2022)
Research Scientist, Educational Technology, IIT Bombay (2020 - 2021)
Postdoctoral Research Fellow, Department of Computer Science, Vanderbilt University (2018 -2020)
E-Mail: shitanshu [AT] iitb.ac.in; shitanshu.iitb [AT] gmail.com
Mobile: +91 9892709481
Ethics in AI-in-Education (AIED) - Broad Research Question: Can “ethical AI” be implemented for social-emotional learning (SEL)?
With the digital transformation in the educational space, there is a need for SEL competencies to be delivered digitally. Technology is already addressing the problem of delivering instructions digitally and helping with extracting learning insights. However, for the SEL instructions to be more effective, inclusive, and equitable, digital SEL capacity-building programmes need to harness ethical AI’s power.
“Ethical AI” emphasizes ethical considerations in determining justifiable and unjustifiable usage of AI. UNESCO MGIEP respects ethical guidelines on fundamental values, individual rights, privacy, non-discrimination, and non-manipulation; therefore, it becomes essential for us to adhere to ethical considerations of AI when enhancing FramerSpace for SEL. Ethical AI has its limitations; for example, most of the AI algorithms that outperform traditional rule-based or statistics-based methods are “black box,” i.e., it’s hard to know exactly how an algorithm arrived at its prediction.
At UNESCO MGIEP, I, with my team, seek to investigate the challenges and limitations associated with Ethical AI and explore how to build ethics into the AI-based educational systems. This is especially pertinent in the context of AI for SEL, as analyzing social-emotional aspects of learners would require capturing more sensitive and diverse learner data from multiple modalities. Starting with exploring the answer to the broad research question, “Can we build ethics into the AI system?”, we aim further to answer other research questions specific to the SEL context.
Keywords: AIED, Ethical AI, Social-Emotional Learning, Technology Enhanced Learning Environment
Programming-RIO: Developing Computational Thinking through Programming Real-life IoT Objects. [ACM India Supported Project 2020-21]:
The project aims at developing a better understanding of how can the platforms like IFTTT or Alexa Routines that help in configuring complex if-then-else behaviors of real-world Internet-of-Things Objects (RIO) can help in supporting students’ learning of computational thinking (CT). We call these platforms “Programing-RIO platforms”. We aim at devising pedagogies around these platforms and the IoT devices to develop CT in students. With the broader research objective of exploring the impact of Programming-RIO on middle school students’ development of CT, our specific research objectives for the first year of this project is to: (i) Evaluate the possibility of using Programing-RIO platforms like IFTTT as a medium for teaching and learning of CT; (ii) Identify the nuances of using Programing-RIO platforms like IFTTT as a medium for teaching and learning of CT due to their situatedness and impact of IoTs as tools to think with; (iii) Compare the effectiveness of learning CT with Programing-RIO platforms to other visual and text-based approaches. My contribution to the project till now was that I co-proposed the idea and co-drafted the proposal. The proposal has been accepted for execution between December 2020 – December 2021.
Keywords: Computational Thinking, Internet-of-Things, Situated Learning, Authentic Contexts, 4E Cognition, Physical Manipulables, IFTTT, GoogleHome, Alexa Routines
Immersive Training of Indian In-service Faculty to Conduct Action Research through a Large Scale Multi-institutional Investigation of Student Interests in Computing Programmes.[ACM India Supported Project 2020-21]
This project is supported by ACM India and aims at providing training to computing faculty in computing education research and building a community of researchers and practitioners engaged in knowledge-sharing. Specifically, I proposed an immersive training of in-service computing faculty (particularly faculty outside Tier-1 institutions) to conduct action research in their classrooms, which includes performing relevant data collection and analyses, recognizing the value of such research in improving the learning outcomes of their students, etc. The immersive element of this training will be a substantial hands-on component and seeks to empower faculty to conduct in-situ action research to collect and analyze their own students’ data to make data-informed critical reflections to improve their teaching effectiveness. The data collected by the diverse pool of participating faculty during hands-on training, synergistically, offers an opportunity to investigate research questions that are worth studying in a diverse institutional context. For this specific project, we propose a large-scale, multi-institutional data collection to investigate students' interests currently enrolled in computing programmes to answer two specific questions, viz., (1) Why do students enroll in computing programs in India? (2) How do student expectations match their experience after they join a computing program? My contribution to the project till now was that I proposed the idea and co-drafted the proposal. The proposal has been accepted for execution between December 2020 – December 2021.
Keywords: CS Education Research, Curriculum, India, Large Scale Study, Large Scale Faculty Training, Action Research
Embodied Narratives of Critical Thinking (ENaCT): An Action-based Framework for the Learning and Analytics of Critical Thinking[Research Collaboration for Kyoto University SPIRITS2020 project]:
Abstract: The motivation for this project came from the observations that there has been a misinformation overload related to the COVID19 in society, and it was important to work towards a technology that can help kids hone their critical thinking skills and can also help researchers and teachers to capture students’ Critical Thinking (CrT) processes. I started in July 2020, along with my collaborators from Kyoto University, Japan; EPFL, Switzerland; Roskilde University, Denmark; and IIT Madras, proposed a new framework: Embodied Narratives of Critical Thinking (ENaCT). The framework will help the community conceptualize the learning of CrT and analytics to assess CrT, in a technology-enhanced environment. In the context of a CrT activity, the framework bridges the perspectives of embodied cognition, aligning actions that constitute learning, with learning analytics approaches, to measure and build embodied narratives of the learning process. We published and illustrated the components of this new framework at 28th International Conference on Computers in Education (ICCE 2020) . My responsibility in the project is primarily towards the analytics part of the framework.
Keywords: Critical Thinking, Learning Framework, Analytics Framework, Embodied Learning
Modeling Learner’s Cognitive and Psychomotor Processes in Dismounted Battle Drills:
Abstract: The focus of my research group at Vanderbilt University is on studying open ended learning environments (OELE). The broader objective of this project was to develop an intelligent OELE that could support team training for dismounted battle drills for US army personnel using virtual and augmented reality environments. Examples of dismounted battle drills include operations such as “enter and clear a room” and “react to direct fire contact” for urban warfare conducted by the armed forces. These operations require the soldiers to develop effective psychomotor and cognitive skills and cognitive strategies along with the ability to work in teams. For example, soldiers are required to identify and differentiate enemy combatants from noncombatants inside the threat area, and at the same time, they have to provide cover for the other team members. I developed a learner modeling framework to evaluate psychomotor, cognitive, strategic, and affective processes. The framework uses data from multiple modalities, such as computer logs, video analysis, eye tracking, and physiological sensors. In particular, I proposed performance and effectiveness measures and metrics for the Squad Advanced Marksmanship Trainer (SAM-T), a virtual battle drill practice environment for soldiers. The framework was submitted to, reviewed and accepted by the Army Research Lab, US government.
Studying Learner’s Problem-Solving Strategies and Affective States in an Open Ended Learning Environment using Multi-modal Learning Analytics:
Abstract: To study the interaction between middle school learners’ affective states, their cognitive strategies and learning gains in an open ended learning environments (OELEs), I collected data from facial emotion detector, eye gaze patterns, action log data, videos from screen capture software and human observation of affective states to perform multimodal learning analytics. Our first step was to align the pre-processed data from multiple sensors. Then analyze the interaction between learner’s performance and emotions. We collected gaze patterns, facial emotions and log data from 60 students working on an OELE called Betty’s Brain. Different analyses performed on the data helped us in unfolding interesting insights about relationships among learner’s cognition and emotion data. One of such analysis helped us model the relationships between learners’ basic and achievement emotions during learning in a computer based OELE. Another analysis helped us in obtaining affect-based proxies for learners’ cognitive behaviors in an OELE. Currently, I am continuing my work on this data in collaboration with two graduate students from Vanderbilt with an aim to study the students’ learning and problem-solving behaviors using students’ action logs and gaze data to evolve a framework for developing personalized scaffolds to foster strategic learning. I am employing computational techniques such as sequence mining on the action logs to extract differentially frequent behavioral patterns among different levels of performers and then zoom into their cognitive strategies using their gaze patterns. The findings from this research will inform the designs of cognitive and affective scaffolds in Betty’s Brain.
Keywords: Computer-Based Learning Environment, Multimodal Learning Analytics, STEM Learning, Causal Reasoning
DOCTORAL THESIS: Fostering Students' Cognitive Processes of Knowledge Integration through Exploratory Question Posing: July 2012 – January 2018
Abstract: When students encounter new knowledge, it is often fragmented and not well connected to their existing knowledge. It is known that students need to integrate knowledge pieces effectively to develop a deep and cohesive understanding of any topic. My PhD thesis's focus was on designing a pedagogy and developing a corresponding online self-learning environment to improve the cognitive processes associated with knowledge integration (KI) in learners. These cognitive processes include eliciting prior knowledge, focusing on new knowledge, and distinguishing among knowledge. The proposed pedagogy used student’s question-posing as a cognitive tool to help them foster cognitive processes of KI. In the initial phase of my research, I found that exploratory question-posing can be used as a cognitive-tool to trigger these cognitive processes. Thereafter, I designed a learning environment named Inquiry-based Knowledge Integration Trainer (IKnowIT). I carried out a series of exploratory qualitative and quantitative studies with sophomore CS engineering students, where participants performed the learning activities in the context of topics from the data structures domain. Publications that came out of the PhD thesis were from all the three research domains, viz., computing education, learning science, and educational technology research. A few of the peer reviewed publication avenues were, Innovation and Technology in Computer Science Education (ITiCSE), Journal of Research and Practice in Technology Enhanced Learning (RPTEL) and International Conference on Learning Science (ICLS).
Exploring Indian Computer Science (CS) Undergraduate Student’s Conception about the CS major. June 2015 - September 2016.
Abstract: In the year 2016, in the International Computing Education Research (ICER) 2016 conference, Dr. Mike Hewner and I co-published a research report on Indian CS students’ conceptions about computer science major. Applying grounded theory methods, we unfolded how the Indian educational system and the widespread perception about careers in CS-related fields in India, lead to student’s decision to choose CS as their major for undergraduate studies.
My Role: I co-designed the study, collected data (interviewed), co-performed the grounded theory analysis, co-authored the research report, presented at ICER 2016, Melbourne, Australia.
International Working group on “New Horizons in the Assessment of Computer Science at School and Beyond.” Vilnius, Lithuania, Feb - September 2015
Abstract: A working group, comprised of Computing Education researchers from multiple countries, collaborated, and published a research report in the Innovation and Technologies in Computer Science Education (ITiCSE) 2015. As a working group, we reviewed the state of the CSEd field and made concrete, achievable proposals for developing shared, high-quality assessments for computer science. Central to this proposal was the collaborative platform VIVA (the Vilnius collaboratively coded and Validated computer science questions/tasks for Assessment). Two requirements were key to VIVA: 1) support for multiple competency frameworks so that the contributors can meta-tag assessment resources with respect to the framework they are most familiar with, and 2) support for crowdsourcing the validation of each question/task and its mapping to competencies. The use of a taxonomy of questions/tasks type that has been mapped to computational thinking concepts and competency framework was proposed.
My Role: I was one of the working group members and my role was to develop the VIVA platform.
Institute - level project: Incorporating Educational Technology in CS1 and CS2. Mumbai, India, 2012 - 2015.
Abstract: My department (IDP in EdTech) at IIT Bombay had carried out several efforts to incorporate innovative pedagogies and technologies for improving the teaching-learning of undergraduate learners from other departments within IIT Bombay, especially Computer Science. These projects include: (i) Using problem-posing activities in CS1 class; (ii) Using Scratch (a visual programming language) based introduction to programming (CS1) for novice learners; (iii) using “think-pair-share” pedagogy in CS2 (data structures) class, etc.
My Role: I administered the research and conducted the evaluation studies. The empirical studies and findings have been published in peer-reviewed conference proceedings
SQDL: Student Question Driven Learning. Mumbai, India, 2013 – 2015
Under the guidance of Prof. Sridhar Iyer, I designed a pedagogy that uses student question-posing to enable student-directed learning. The pedagogy proposes to use the questions posed by the students to decide which content has to be taught in the next instruction. The pedagogy has been empirically tested primarily on two factors: (i) How much course-coverage is achieved in an SQDL-based classroom; (ii) What are its effects on students’ affective dimensions such as their interests, motivation, and belongingness to the instructions.
My Role: I designed the pedagogy, implemented the study, and collected-analyzed the data, under the guidance of Prof. Sridhar Iyer.
International Working group on “Exploring Link between Early Developmental Activities and Computing Proficiency.” Feb 2017 - Present
Abstract: As countries adopt computing education for all pupils from primary school upwards, there are challenging indicators: significant proportions of students who choose to study computing at universities fail the introductory courses, and the evidence for links between formal education outcomes and success in CS is limited. We hypothesized that early childhood activities can have effects on the development of an individual’s computational skills. A working group comprised of Computing Education researchers from multiple countries was formed to study this link between early childhood activities and computing proficiency in adulthood. In this study, we collected and analyzed over 1300 responses to a multi-institutional and multi-national survey that we developed. The survey captured the enjoyment of early developmental activities such as childhood toys, games, and pastimes between the ages 0 — 8 as well as later life experiences with computing. We identified unifying features of the computing experiences in later life and attempted to link these computing experiences to childhood activities. This research is still under progress, and it is hoped that it will feed into early years and primary education, and thereby improve computing education for all.
My Role: Initially, I volunteered as a non-official member, actively participated in deliberations, administered the data collection from the Indian population, and assisted the data analyses in Bologna. Currently, I am one of the official collaborators and conducting the analysis and related research work.