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Hazra Imran

  • Department of Computer Science
  • University of British Columbia

Profile

Hazra Imran is an Instructor of Computer Science at UBC with over 11 years of experience in Academic and Research. Hazra has a passion for teaching and enjoys interacting with her students. Her research mainly focuses on Advanced Adaptivity and Personalization, Collaborative Recommendation and Personalized Web Based Learning Systems.

She completed her postdoctoral fellowship at Athabasca University in Canada, funded by MITACS under the guidance of Prof. Sabine Graf and Prof. Kinshuk at Athabasca University. Her research had two folded facets. One of the aspect of research dealt with an intelligent application in the e-learning area aimed at personalizing the learning experience to the real needs of each student. The other aspect was to support teachers by providing them with tools which can provide them insights about their learners and the courses to understand the student's behavior and to improve their courses.

She has instructed over fifty courses in computer science at UBC (Canada), Langara College (Canada), Douglas College (Canada) and Hamdard University (India), with a class size ranges from 35 to 160. As an Assistant Professor of Computer Science at Hamdard University, she has supervised several graduate and under graduate students. Her objective as a teacher is to motivate her students to develop their own learning interests and critical thinking. In particular, teaching a wide range of computer science courses during her teaching career has made Hazra aware of the needs and interests of diverse student body. To promote students learning, she has integrated many innovative techniques in her teaching.

Outside the academic world, she enjoys exploring new places, listening music and food. Hazra and her husband, Imran, are parents of two young kids, Inaayah and Adheem.

Academic Positions

  • Present Sep 2016

    Sessional Lecturer

    Department of Computer Science, University of British Columbia

  • Present Dec 2015

    Sessional Lecturer

    Computer Science, Langara College, BC, Canada

  • Aug 2016 Jan 2016

    Sessional Lecturer

    Computer Science, Douglas College, BC, Canada

  • Dec 2015 Apr 2015

    Research Assistant and Data Analyst

    Athabasca University, Edmonton, AB, Canada

  • Mar 2015 Mar 2013

    Post-Doctoral Fellow

    Athabasca University, Edmonton, AB, Canada

  • Jan 2013 Oct 2011

    Instructor

    Computer Science, PACE Canada College, BC, Canada

  • Aug 2011 Jan 2006

    Assistant Professor

    Department of Computer Science, Hamdard University, New Delhi, India

  • Sep 2003 Dec 2003

    Teaching Assistant

    Computer Science,Banasthali University, Rajasthan, India

Education & Training

  • Ph.D. 2012

    Ph.D. in Computer Science (Information retrieval)

    School of Computer and Systems Sciences Jawaharlal Nehru University (JNU), New Delhi, India

  • Master of Technology2005

    Master of Technology, Computer Science

    Banasthali University, Rajasthan, India

  • Bachelor of I.T.2003

    Bachelor of Information Technology,

    New Delhi, India

Honors, Awards and Grants

  • 2013-2015
    Post-doctoral Research Fellowship
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    Post-doctoral Research Fellowship of $125,000 from MITACS Elevate (Canada)
  • 2014-2016
    Research Project - Intelligent Assistants: promoting support teaching activities in virtual teaching and learning environments
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    Funding of R$ 46,790 (~ CAD18,000) from CNPq-SETEC/MEC Nº 17/2014 -Process 467935/2014-9 for project “Intelligent Assistants: promoting support teaching activities in virtual teaching and learning environments”.
  • 2008
    Best Paper Nomination
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    Best paper nomination “A Trainable Document Summarizer Using Bayesian Classifier Approach” in IEEE International Conference on Emerging Trends in Engineering and Technology, India
  • 2003-2005
    Scholarship from Ministry of Human Resource Development (MHRD), Government of India
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    Scholarship of INR 2,00,000 (~ 3600 CAD) from Ministry of Human Resource Development (MHRD), Government of India during Master studies.
  • 2003
    Scored 95.60 percentile in GATE
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    Scored 95.60 percentile in Graduate Aptitude Test in Engineering (GATE) (all India examination)

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Teaching

Teaching is more than imparting knowledge, it is inspiring change. Learning is more than absorbing facts, it is acquiring understanding.
-William Arthur Ward



  • 2020
    CPSC 304 : Introduction to Relational Databases - W2
  • 2019
    CPSC 322 : Introduction to Artificial Intelligence - W1
  • 2019
    CPSC 304 : Introduction to Relational Databases - S1
  • 2019
    CPSC 304 : Introduction to Relational Databases - W1
  • 2018
    CPSC 304 : Introduction to Relational Databases - W2
  • 2018
    CPSC 304 : Introduction to Relational Databases - W1
  • 2017
    CPSC 304 : Introduction to Relational Databases - W2
  • 2016
    CPSC 304 : Introduction to Relational Databases - W1

Research Summary

Learning management systems (LMS) are typically used by large educational institutions and focus on supporting instructors in managing and administrating online courses. However, such LMS typically use a “one-size-fits-all” approach where same course content and structure is delivered to all learners. But, each learner has different characteristics, and therefore, a “one size fits all” approach does not support most learners particularly well. One of the possible ways to support each learner individually based on his/her characteristics is the use of personalization. Personalization in learning management systems (LMS) occurs when such systems tailor the learning experience of learners such that it fits their profiles, which helps in increasing their performance within the course and the quality of learning. A learner's profile can, for example, consist of his/her learning styles, goals, existing knowledge, ability, and interests.

The aim of the research was to offer rich adaptivity and personalization by integrating recommender systems into existing LMS, enabling an LMS to adapt courses not only based on learner's individual profile (learning styles, prior knowledge, expertise level and performance) but also based on what worked well for learners with a similar profile in similar situations to increase learner's efficiency, performance and/or satisfaction. The research dealt with an intelligent application in the e-learning area aimed at personalizing the learning experience to the real needs of each learner. Such advanced personalization can help learners in many ways such as reducing the learning time without negative impact on their marks, improving learning performance as well as increasing the level of satisfaction. This research aimed to improving the overall quality of learning by providing personalized recommendations to learners as well as providing detailed insight about the course and learners to the teachers.

Interests

  • User Adaptive Systems
  • Recommender Systems
  • Personalized Web-Based Systems
  • Learning Analytics
  • Information Retrieval

Research Projects

  • 2019 – Present

    A Personalized Profile Based Gamification System

    The research is envisaged to contribute significantly to wide-ranging benefits for the education sector by improving the overall quality through providing personalized learning experiences to the learners based on their individual profiles in a gamified environment.
    Hazra Imran – Coordinator

    2014 – 2018

    Intelligent Assistants: promoting support to teaching activities in virtual teaching and learning environments

    The project aims to develop intelligent assistants to assist teachers in improving their practices in the teaching in learning virtual environment
    Julia Marques Carvalho da Silva – Coordinator
    Hazra Imran - Member ; Mauricio Covolan Rosito - Member

  • 2013-2015

    PLORS – Personalized Learning Object Recommender System

    The project deals with an intelligent application in the e-learning area aimed at personalizing the learning experience to each learner. Based on the aim, the research focuses on using a recommendation mechanism to provide recommendations of which learning objects within a course are more useful for learners, considering the learning object he/she is visiting as well as the learning objects visited by other learners with similar profiles.
    Hazra Imran-Coordinator
    Sabine Graf- Member

  • 2013-2015

    RBRS - Rule Based Recommender System

    The project aims to develop a recommender system for students in student-centered pedagogy. The recommender system helps astudentin making appropriate selections of tasks in the course.The recommender system considers the different difficulty levels of tasks and recommends tasks based on the learner’s previous performance, his/her initial plan on what tasks to select, and the performance of similar learners.
    Hazra Imran-Coordinator
    Sabine Graf- Member

  • 2013-2015

    WBLORS - Web Based Learning Object Recommender System

    The project aims to develop a recommender system for students to recommend additional learning objects from web based on their learning styles as well as the recommended learning objects that worked well for other similar learners.
    Hazra Imran-Coordinator
    Sabine Graf- Member

  • 2013-2015

    VAT- Visualization and Analytical Tool for teachers

    The project aims to provide support to teachers by providing them the valuable information and visualization about their students and courses. For this purpose, a tool is developed to support reflection and improvement of teaching practices.
    Hazra Imran-Coordinator
    Sabine Graf- Member

  • 2013-2015

    AAT-Academic Analytical Tool

    The project aims to provide instructors and learning designers with some basic access to log data
    Sabine Graf- Coordinator
    Hazra Imran-Member

Selected Publications

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VAT-RUBARS: A Visualization and Analytical Tool for a Rule-Based Recommender System to Support Teachers in a Learner-Centered Learning Approach. International Conference on Smart Learning Environments (ICSLE).In State-of-the-Art and Future Directions of Smart Learning, 31-38, Springer Berlin Heidelberg

Imran, H., Ballance, K., Silva, J., Kinshuk, Graf, S.
Conference Papers Acceptance rate: 30%

Co-occurrence Based Predictors for Estimating query difficulty. In Proceeding of International Conference on Data Mining Workshops. 867-874. Australia, IEEE Computer Society. [Acceptance rate: 19.2%, Google Scholar Citations: 15]

Imran, H., and Sharan, A.
Workshops

Dedication versus Course's Completion: an analysis through Moodle LMS logs. Revista Campus Virtuales

Imran, H.,Scariot, Ana P., Andrade, Fábio G., Piresa, D., Fernandes, A., and Silva, J.
Journal Paper Submitted

Genetic Algorithm Based Model for Effective Document Retrieval.In AO, S., Castillo O., Huang X. (Eds.),Intelligent Control and Computer Engineering (pp.191-201). The Netherland, Springer.

Imran, H. and Sharan, A.
Book Chapter[ISBN: 978-94-007-0285-1 (Print) 978-94-007-0286-8 (Online),Google Scholar Citations: 2]

PLROS: A Personalized Learning Object Recommender System.Vietnam Journal of Computer Science, 1-11

Imran, H., Belghis-Zadeh, M., Ting-Wen Chang, T.W., Kinshuk, Graf, S.
Journal Paper

A study on the variables for prediction of not graduating students in courses supported by Virtual Environments for Teaching and Learning. RENOTE. Magazine New Technologies in Education.

SILVA, Julia Marques ; IMRAN, H.
Conference Papers
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Proven strategies for harnessing the power of social media to drive social change

Many books teach the mechanics of using Facebook, Twitter, and YouTube to compete in business. But no book addresses how to harness the incredible power of social media to make a difference. Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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From Co-occurrence to Lexical Cohesion for Automatic Query Expansion. International Journal of Computational Linguistic and Applications, 3(1), 107-119

Imran, H.and Sharan, A.
Journal Paper[Open Access; ISSN 0976-0962]

Selecting Effective Expansion Terms for Better Information Retrieval.Special issue on Web Semantics of International Journal of Computer Science & Applications, 7(2), 52-64

Imran, H. and Sharan, A.
Journal Paper [Open Access; ISSN 0972-9038, Citations : 3]

Abstract

Although a substantial amount of research has examined the constructs of warmth and competence, far less has examined how these constructs develop and what benefits may accrue when warmth and competence are cultivated. Yet there are positive consequences, both emotional and behavioral, that are likely to occur when brands hold perceptions of both. In this paper, we shed light on when and how warmth and competence are jointly promoted in brands, and why these reputations matter.

Toward recommending learning tasks in learner-centered approach. InProceedings of the International Conference on Smart Learning Environments (ICSLE). Lecture Notes in Educational Technology, July 2014, 337-344, Hong Kong, Springer Berlin Heidelberg

Imran, H., Belghis-Zadeh, M., Ting-Wen Chang, T.W., Kinshuk, Graf, S.
Conference Papers Acceptance rate: 30%

A Framework to Provide Personalization in Learning Management Systems through a Recommender System Approach. In: Nguyen, N.-T., Attachoo, B., Trawinski, B., Somboonviwat, K. (Eds.) Proceedings of the 6th Asian Conference on Intelligent Information and Database Systems (ACIIDS). Lecture Notes in Artificial Intelligence (LNAI), April 2014, Vol. 8397, 271-280, Bangkok, Springer International Publishing

Imran, H., Hoang, Q., Chang, T. W., Kinshuk and Graf, S.
Conference Papers Acceptance rate: 30%

A Rule-Based Recommender System to Suggest Learning Tasks. In Proceedings of the International Conference on Intelligent Tutoring Systems (ITS), Lecture Notes in Computer Science (LNSC), June 2014, Vol. 8474, 672-673, Honolulu, US, Springer International Publishing

Imran, H.,Belghis-Zadeh, M. Ting-Wen Chang, T.W., Kinshuk, Graf, S.
Conference Papers Acceptance rate: 30%

Improving Effectiveness of Query Expansion Using Information Theoretic Approach. In García-Pedrajas, N., Herrera, F., Fyfe, C., Benítez Sánchez, J.M., Ali, M. (Eds.) Proceedings of theInternational Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA-AIE), Lecture Notes on Computer Science (LNCS), June 2010, Vol. 6097, 1-11, Spain, Springer Berlin Heidelberg [Ranked 46thamong top 701 Computer Science Conference; Acceptance rate: 40%; Google Scholar Citations: 2]

Imran, H.and Sharan, A.
Conference Papers Acceptance rate: 30%

A Trainable Document Summarizer Using Bayesian Classifier Approach. In Proceedings of the International Conference on Emerging Trends in Engineering and Technology (ICETET), July 2008, 1206-1211, India, IEEE.[Nominated for Best Paper Award; Google Scholar Citations: 1]

Imran, H. Sharan, A. & Joshi, M.
Conference Papers

A Framework for Efficient Document Ranking Using Order and Non Order Based Fitness Function. In Proceedings of the International MultiConference of Engineers and Computer Scientists, March 2010, Vol. 1, 71-76, Hong Kong,Newswood Limited.[Acceptance rate: 56%; Google Scholar Citations: 1]

Imran, H.& Sharan, A.
Conference Papers

Thesaurus and query Expansion.International Journal of Computer science & Information Technology (IJCSIT), 1(2), 89-97.

Imran, H. and Sharan, A.
Journal Paper [Open Access; ISSN 0975-3826; Acceptance Rate-Less than 20%; Google Scholar Citations: 44]

Abstract

Although a substantial amount of research has examined the constructs of warmth and competence, far less has examined how these constructs develop and what benefits may accrue when warmth and competence are cultivated. Yet there are positive consequences, both emotional and behavioral, that are likely to occur when brands hold perceptions of both. In this paper, we shed light on when and how warmth and competence are jointly promoted in brands, and why these reputations matter.

Teaching

Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.



Contact & Meet Me

  • Address: Department of Computer Science
    The University of British Columbia
    2366 Main Mall
    Vancouver, B.C.
    Canada V6T 1Z4

      hazra@cs.ubc.ca
  •    hazrabano@gmail.com
  •   linkedin.com/in/hazraimran

At My Office

You can find me at my office located at 2366 Main Mall. Please check office number in the course outline.

I am at my office during my office hours, but you may consider sending an email to fix an appointment.