Fatemeh Salehian Kia

Assistant Professor of Teaching

About

Fatemeh Salehian Kia is an Assistant Professor of Information Science in the educational leadership stream at the University of British Columbia, where she conducts research at the intersection of technology and education to enhance our understanding of how people learn. She is also an affiliated researcher at the School of Information, University of Michigan, Ann Arbor.

Her research primarily focuses on learner engagement with information through educational technology, with a specific emphasis on quantifying the learning context. Through a diverse range of methods, including experimental approaches, she investigates how learners interact with information when utilizing educational technology. Her research explores the various factors that contribute to effective learning, encompassing individual attributes, learning environments, and contextual elements.

As a multidisciplinary researcher with a background in computer science, design, and cognition, she actively contributes to the field of learning analytics by integrating data science, learning science, and human-computer interaction. Her contributions encompass the development of novel data sources, computational models, and innovative learning technologies. Her work has been published in esteemed conferences and journals within the domains of learning analytics and human-computer interaction. She has also conducted research at renowned institutions such as UC Berkeley, the University of North Carolina at Chapel Hill, and the University of South Australia.

In addition to her focus on learner engagement, another significant aspect of her work revolves around leveraging learning analytics to support productive learning experiences. She has made substantial contributions to two impactful projects: OnTask, an adaptive learning technology designed to provide personalized feedback to instructors, and My Learning Analytics (MyLA), a student-facing dashboard that facilitates self-regulated learning. Her research is dedicated to evaluating the effectiveness of these technologies in enhancing students’ learning outcomes.

At UBC, her research encompasses two primary areas of focus. Firstly, she employs a theoretical foundation to gain deeper insights into the learning processes, particularly in the context of increasing human interactions with virtual learning environments and the consequential accumulation of massive digital footprints. Secondly, she utilizes innovative technologies and computational methods to identify and address undesirable patterns of learning behaviors on a large scale, thereby promoting more effective learning environments.


Teaching


Research

  • Learning Analytics
  • AI in Education
  • Human-Centred Design

Fatemeh Salehian Kia

Assistant Professor of Teaching

About

Fatemeh Salehian Kia is an Assistant Professor of Information Science in the educational leadership stream at the University of British Columbia, where she conducts research at the intersection of technology and education to enhance our understanding of how people learn. She is also an affiliated researcher at the School of Information, University of Michigan, Ann Arbor.

Her research primarily focuses on learner engagement with information through educational technology, with a specific emphasis on quantifying the learning context. Through a diverse range of methods, including experimental approaches, she investigates how learners interact with information when utilizing educational technology. Her research explores the various factors that contribute to effective learning, encompassing individual attributes, learning environments, and contextual elements.

As a multidisciplinary researcher with a background in computer science, design, and cognition, she actively contributes to the field of learning analytics by integrating data science, learning science, and human-computer interaction. Her contributions encompass the development of novel data sources, computational models, and innovative learning technologies. Her work has been published in esteemed conferences and journals within the domains of learning analytics and human-computer interaction. She has also conducted research at renowned institutions such as UC Berkeley, the University of North Carolina at Chapel Hill, and the University of South Australia.

In addition to her focus on learner engagement, another significant aspect of her work revolves around leveraging learning analytics to support productive learning experiences. She has made substantial contributions to two impactful projects: OnTask, an adaptive learning technology designed to provide personalized feedback to instructors, and My Learning Analytics (MyLA), a student-facing dashboard that facilitates self-regulated learning. Her research is dedicated to evaluating the effectiveness of these technologies in enhancing students’ learning outcomes.

At UBC, her research encompasses two primary areas of focus. Firstly, she employs a theoretical foundation to gain deeper insights into the learning processes, particularly in the context of increasing human interactions with virtual learning environments and the consequential accumulation of massive digital footprints. Secondly, she utilizes innovative technologies and computational methods to identify and address undesirable patterns of learning behaviors on a large scale, thereby promoting more effective learning environments.


Teaching


Research

  • Learning Analytics
  • AI in Education
  • Human-Centred Design

Fatemeh Salehian Kia

Assistant Professor of Teaching
About keyboard_arrow_down

Fatemeh Salehian Kia is an Assistant Professor of Information Science in the educational leadership stream at the University of British Columbia, where she conducts research at the intersection of technology and education to enhance our understanding of how people learn. She is also an affiliated researcher at the School of Information, University of Michigan, Ann Arbor.

Her research primarily focuses on learner engagement with information through educational technology, with a specific emphasis on quantifying the learning context. Through a diverse range of methods, including experimental approaches, she investigates how learners interact with information when utilizing educational technology. Her research explores the various factors that contribute to effective learning, encompassing individual attributes, learning environments, and contextual elements.

As a multidisciplinary researcher with a background in computer science, design, and cognition, she actively contributes to the field of learning analytics by integrating data science, learning science, and human-computer interaction. Her contributions encompass the development of novel data sources, computational models, and innovative learning technologies. Her work has been published in esteemed conferences and journals within the domains of learning analytics and human-computer interaction. She has also conducted research at renowned institutions such as UC Berkeley, the University of North Carolina at Chapel Hill, and the University of South Australia.

In addition to her focus on learner engagement, another significant aspect of her work revolves around leveraging learning analytics to support productive learning experiences. She has made substantial contributions to two impactful projects: OnTask, an adaptive learning technology designed to provide personalized feedback to instructors, and My Learning Analytics (MyLA), a student-facing dashboard that facilitates self-regulated learning. Her research is dedicated to evaluating the effectiveness of these technologies in enhancing students’ learning outcomes.

At UBC, her research encompasses two primary areas of focus. Firstly, she employs a theoretical foundation to gain deeper insights into the learning processes, particularly in the context of increasing human interactions with virtual learning environments and the consequential accumulation of massive digital footprints. Secondly, she utilizes innovative technologies and computational methods to identify and address undesirable patterns of learning behaviors on a large scale, thereby promoting more effective learning environments.

Teaching keyboard_arrow_down
Research keyboard_arrow_down
  • Learning Analytics
  • AI in Education
  • Human-Centred Design