Ashraf Alam

@iitkgp.ac.in

Ph.D. Scholar, Rekhi Centre of Excellence for the Science of Happiness
Indian Institute of Technology Kharagpur, India



                                   

https://researchid.co/ashraf_alam

I am proud to have been recognized as one of Stanford/Elsevier's Top 2% Scientists of the World, a rare distinction that reflects my commitment to advancing knowledge in my field. Currently, I am associated with IIT Kharagpur. In October 2021, I was honored with the "Emerging Researcher of the Year" award during the "Education Icon Awards," a prestigious initiative by the Indian Council of Social Science Research (ICSSR), Government of India.

Throughout my career, I have published over 100 research papers in reputed international journals, all of which are indexed in SCOPUS and/or Web of Science. These publications, many of which have appeared in renowned platforms like Taylor and Francis, Elsevier, Springer, Wiley, Emerald, IEEE, and Sage, reflect the diversity and depth of my research interests. In addition, I have been fortunate to share my work through invited talks and presentations at more than 120 national and international conferences and seminars.

RESEARCH, TEACHING, or OTHER INTERESTS

Education, Artificial Intelligence, Psychology, Public Administration

51

Scopus Publications

Scopus Publications

  • Effect of the subject - ‘Happiness Engineering’ on Indian senior secondary school students
    Ashraf Alam and Atasi Mohanty
    Malque Publishing
    The objective of this research is to investigate the implications of teaching Happiness Engineering subject on various positive psychological outcomes, including subjective well-being, prosocial behavior, and life satisfaction among students enrolled in the 11th and 12th grades, hailing from two senior secondary schools situated in the Bokaro district of Jharkhand, India. The research involved 216 participants from seven classes, who were randomly assigned to one of two conditions: HE (Happiness Engineering) and Control. Participants were selected such that students who took Happiness Engineering as a compulsory subject were part of the HE groups, and those who did not, were part of the Control group. The researchers investigated the development and expression of overall well-being in students, including subjective well-being, gratitude, prosocial behavior, and life satisfaction. The effect of this intervention (teaching of Happiness Engineering subject) was then compared to the control condition (where participants did not engage in Happiness Engineering classes). The results of the study revealed several significant findings. First, participants who were part of the HE intervention group reported higher levels of optimism and life satisfaction and lower levels of negative affect. This suggests that the act of consciously focusing on and appreciating positive aspects of one’s life can lead to increased well-being and decreased negative emotions. An exceptionally profound revelation came to light concerning the robust correlation between HE classes and contentment regarding the scholastic milieu. It is noteworthy that, both directly after the implementation of the intervention and during the subsequent assessment at the end of a four-week period, the cohort exposed to the HE intervention exhibited elevated levels of satisfaction in their educational environment in contrast to the control condition. The study unveiled that Happiness Engineering is an effective school subject that has the potential to profoundly influence young adults in perceiving and engaging with their school environment, ultimately fostering a more positive and enriching educational experience.






  • Developing ‘Happiness Engineering’ Subject for the Schools in India: Designing the Pedagogical Framework for a Sustainable Happiness Curriculum
    Ashraf Alam and Atasi Mohanty
    QUBAHAN
    The aim of this research was to develop the ‘Happiness Engineering’ subject by designing a ‘sustainable happiness curriculum’ and ‘pedagogical framework’ for the schools of India by adopting the whole school approach. Happiness Engineering subject is modelled like any other traditional school subject, e.g., History, Chemistry, or Computer Science. The researchers have prepared it by adopting the scientifically proven ‘global best practices’ exercised in different schools, colleges, and university departments across the globe in ‘sustainability education’, ‘adjectival education’, and ‘well-being education’. It has been adapted and contextualised to be implemented in Indian schools by considering the available infrastructural resources in existing Indian schools and bearing in mind the feasibility of its effective transaction. Experiences of 129 experts from India that included senior secondary school teachers, school counsellors, pedagogical scientists, learning theorists, health experts, people from NGOs, and professors of education, were used to modify and contextualize the prepared curriculum framework for the ‘Happiness Engineering’ subject to effectively cater the needs of Indian senior secondary school students.


  • Metamorphosing Teaching and Learning with Python: A Practical Guide for Teachers Employing Text Data Analysis Using the Bag of Words (BoW) Model
    Ashraf Alam
    IEEE
    This research explores the application of the Bag of Words (BoW) model for text data analysis with the goal of enhancing teaching-learning in the classroom. The BoW model expresses text as a “bag” of its individual words while ignoring word order. The study covers the use of the BoW model toward the creation of intelligent teaching systems. These systems identify areas where students may be having difficulty and offer focused feedback and guidance by examining the language used by students as they work through an issue or subject. The paper uses snippets of Python code as examples and their outputs to demonstrate how the BoW model can be used to improve learning outcomes. The BoW model’s importance in assessing educational resources, developing intelligent tutoring programmes, and analysing student writing is greatly emphasised in the paper.

  • Data-Driven Instructional Practices: Using Behavior Detection and Model Assignment Techniques to Inform Teaching Strategies for School Education
    Ashraf Alam
    IEEE
    An increasingly common method for assessing students’ performance on tests is automated grading. It might potentially free up time for teachers and provide students with fast feedback so they can see where they need to improve. For better learning outcomes, automated grading must be utilized in conjunction with other instructional strategies. In this study, we provide Python codes for factor analysis-based automated grading to analyze students’ performance on tests. The code first loads the evaluation data as a matrix with each row denoting a student and each column denoting an evaluation item. After that, we use factor analysis to find latent variables that affect student performance. We establish a grading system in which each letter grade is assigned a specific threshold score. Afterwards, we assign each student a grade based on their factor scores, which are determined by adding their results for each latent factor. Each student’s grade and overall score are output by the code. Additionally, our automated grading system demonstrated the ability to spot trends in student performance that could guide teaching strategies. Our computerised grading system can potentially save time and give students rapid feedback, but it must be used in concert with other instructional strategies to guarantee successful learning outcomes. Our study emphasises the significance of employing automated grading to supplement human evaluators rather than to replace them. In order to further tailor learning experiences for students, future study might examine the use of automated grading in conjunction with other behaviour detection and model assignment strategies. Additionally, the development of increasingly complex algorithms might make it possible for automated grading systems to spot trends in student performance that are difficult for human assessors to spot.

  • Educational technology: Exploring the convergence of technology and pedagogy through mobility, interactivity, AI, and learning tools
    Ashraf Alam and Atasi Mohanty
    Informa UK Limited
    Abstract Efforts at the intersection of technology and pedagogy converge upon four pivotal axes that collectively delineate the future educational landscape. These axes, namely mobility, interactivity, artificial intelligence (AI), and technological learning tools like games and augmented reality, encompass the domain of educational transformation. The fusion of these elements necessitates the development of a mobile-interactive paradigm that duly acknowledes the learner’s temporal availability and optimal convenience. Currently, technology is already integrated into the educational realm. However, its diverse manifestations across various contexts underscore the urgent need to integrate and amalgamate these facets within pedagogical frameworks that prioritize students’ erudition. This research undertakes a comprehensive analysis of multifarious technological modalities and puts forth a harmonized model that could furnish a foundational structure for classroom instruction. Central to this paradigm is the recognition of the paramountcy of intelligent tutoring systems, which serve to democratize access to tutoring. By imbuing these systems with advanced AI capabilities, learners can benefit from personalized and adaptive support, irrespective of their location or socioeconomic background. Furthermore, the significance of conducting technological experiments cannot be understated, as it allows for the exploration of new frontiers and the subsequent application of findings to “teaching-learning models.” These models harness a diverse range of interaction patterns to enhance the educational experience. By embracing these transformative elements, educational frameworks can better cater to the evolving needs of learners, while intelligent tutoring systems and ongoing technological experimentation serve as cornerstones in advancing the educational journey.

  • Cultural beliefs and equity in educational institutions: exploring the social and philosophical notions of ability groupings in teaching and learning of mathematics
    Ashraf Alam and Atasi Mohanty
    Informa UK Limited
    ABSTRACT This research article examines the widespread practice of ability grouping in educational systems across different countries, exploring its impact on academic achievement and its implications for equity among mathematics students. The findings underscore the urgent need for educational ecosystems to move away from ability grouping and embrace alternative pedagogical approaches that foster growth mindsets, equitable opportunities, and inclusive education for all students. The implications of this article extend beyond the immediate concerns of schools, school organizations, and mathematics education enthusiasts. Particularly, the insights gleaned from this research bear significant relevance to the development of adolescents and youths on a broader scale. The insights provided by this study are relevant to parents, educators, policymakers, and anyone interested in fostering an educational landscape that equips adolescents and young people with the skills, attitudes, and opportunities needed for success in a diverse and complex world.



  • Implications of virtual reality (VR) for school teachers and instructional designers: An empirical investigation
    Ashraf Alam and Atasi Mohanty
    Informa UK Limited
    Abstract The present study involved an experimental inquiry wherein the researcher examined the possible impact of “textual cues” and “summarising scaffolding” on cognitive load, mental model, and learning performance. The study was conducted on a sample of 122 primary school pupils from Hyderabad, India. It commenced on 20 January 2021 and lasted till 28 October 2021. Using a randomization process, the participants were allocated to one of four experimental groups (D1, D2, D3, and D4). The results of the ANOVA analysis indicate that the utilisation of textual cues had a noteworthy and favourable effect on both the learning performance and the mental model. The implementation of summarising scaffolding yielded a remarkable enhancement in the mental model. The absence of significant “interaction effects” suggests that the implementation of immersive virtual reality, accompanied by textual cues or summarising scaffolding, can be advantageous for young learners. These discoveries hold particular significance for stakeholders involved in the field of education, particularly teachers and students, and possess noteworthy ramifications for the development of efficacious immersive learning environments.

  • The Secret Sauce of Student Success: Cracking the Code by Navigating the Path to Personalized Learning with Educational Data Mining
    Ashraf Alam
    IEEE
    The growing need for tailored learning experiences in post-secondary education has resulted in the adoption of educational data mining (EDM) methodologies to derive significant insights from educational data. The existing scholarly literatures suggest the utilisation of adaptive learning algorithms that integrate various data sources, such as student demographic information, academic performance, and physiological data, to offer individualised learning experiences for students. The algorithms have the capability to modulate the tempo of educational content in response to the cognitive burden experienced by students, which is gauged by their brainwave activity. This study explores the application of predictive models, such as classification, regression, and time-series analysis, in detecting patterns and trends in past data for the purpose of forecasting students’ forthcoming academic achievements. Predictive models have the potential to assist educators in making well-informed decisions aimed at enhancing course outcomes. This research introduces an approach to course improvement analytics that utilises diverse data sources, including student academic records, demographic data, and external platforms such as social media and online forums, to optimise educational results. Through the examination of this data, academic professionals can acquire valuable knowledge regarding student involvement, achievement, and conduct. The present study establishes that the utilisation of course improvement analytics yields valuable information regarding student engagement and behaviour, thereby enabling educators to make informed decisions aimed at enhancing students’ learning outcomes.

  • Media Multitasking with M-Learning Technology in Real-Time Classroom Learning: Analysing the Dynamics in Formal Educational Settings for the Future of E-Learning in India
    Ashraf Alam
    IEEE
    Teachers’ ability to integrate digital technology with formal pedagogical approaches is vital because it ensures that students retain the level of concentration required to understand complex arguments and conduct rigorous classroom-led research. The researcher here argues that classroom dynamics are increasingly at risk due to the addictive nature brought about by the pervasiveness of digital devices and social media, even though many studies have acknowledged the importance of technology in this media-rich world and the idea of “learn anytime, anywhere” associated with mobile learning. Due to the lack of comprehensive studies on the effects of technology on education, especially on the effects of “multitasking” on the teacher’s traditional roles as media orchestrators and learning facilitators, this article critically evaluates the existing literature on mobile learning. By discussing the pros and cons of incorporating technology into the traditional classroom, this article further attempts to give impetus to a discussion that has long been overdue

  • Improving Learning Outcomes through Predictive Analytics: Enhancing Teaching and Learning with Educational Data Mining
    Ashraf Alam
    IEEE
    Educational Data Mining (EDM) is a promising area of research that leverages computational methods to improve educational outcomes by extracting valuable insights from vast educational datasets. The purpose of this study is to explore the relationship between EDM and various educational theories, including Learning Analytics Theory (LAT), Educational Psychology Theory, Cognitive Load Theory, Self-Regulated Learning (SRL) Theory, Bloom’s Taxonomy Theory, Multiple Intelligences Theory, Schema Theory, Situated Learning Theory, Zone of Proximal Development Theory, and Connectivism Theory. This scientific research provides a comprehensive overview of each theory, and discusses how EDM can be used to enhance the understanding and application of these theories in educational settings. Through various teaching-learning classroom examples, the study illustrates how EDM can help identify students’ learning styles, strengths, and weaknesses, develop algorithms that adapt to students’ learning needs in real-time, predict students’ future academic performance, identify challenging areas of a course, and provide tailored instruction and support to individual students. The study further demonstrates how EDM can inform the design of effective teaching strategies, and contribute to the development of personalized and adaptive learning environments.

  • Learning on the Move: A Pedagogical Framework for State-of-the-Art Mobile Learning
    Ashraf Alam and Atasi Mohanty
    Springer Nature Singapore




  • Leveraging the Power of 'Modeling and Computer Simulation' for Education: An Exploration of its Potential for Improved Learning Outcomes and Enhanced Student Engagement
    Ashraf Alam
    IEEE
    Modeling and computer simulation has emerged as an important tool in education as it provides a platform for students to engage in hands-on learning experiences that are interactive, immersive, and personalized. In this paper, the researcher explores the applications of modeling and simulation in education as a means of improving learning outcomes and student engagement. This scientific investigation examines the benefits of employing modeling and computer simulation in teaching complex scientific and engineering concepts, developing virtual labs for hands-on learning, personalizing learning experiences, supporting teacher professional development, and assessing student learning and progress. Furthermore, the researcher demonstrates the use of the programming language Python to simulate the behavior of computer algorithms and provide real-world context for learning. The findings of the study suggest that the use of modeling and computer simulation has the potential to significantly enhance student learning outcomes and engagement, as well as to provide a dynamic and interactive learning environment that supports personalization and creativity.


  • Mechanical Properties Enrichment of Glass Fiber Epoxy by Sugarcane Baggage
    Punita Kumari, Ashraf Alam, and Saahil
    Springer Nature Singapore

RECENT SCHOLAR PUBLICATIONS