Kamila Misiejuk
Biographic Data
| ID | 9590358 |
|---|---|
| NAME | Kamila Misiejuk |
| GIVEN NAMES | Kamila |
| FAMILY NAME | Misiejuk |
| SIGNATURE | MISIEJUK K |
| AFFILIATIONS | University of Bergen |
| ORCID | 0000-0003-0761-8703 |
| VERIFIED | Yes |
| TOTAL WORKS | 8 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 8 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Do modes of presence matter? regulation and participation in graduate students’ hybrid synchronous group-based collaboration
STRUCTURED Abstract Background Synchronous hybrid education offers flexibility and accessibility, but can also pose challenges for students in regulating group work and ensuring equal participation in collaborative activities. Understanding how students address the challenges of regulation and participation in hybrid collaboration settings is critical for designing and supporting students for hybrid education. Aims This exploratory study examines…
Human-AI collaboration or obedient and often clueless AI in instruct, serve, repeat dynamics
While research on human-AI collaboration exists, it mainly examined language learning and used traditional counting methods with little attention to evolution and dynamics of collaboration on cognitively demanding tasks. This study examines human-AI interactions while solving a complex problem. Student-AI interactions were qualitatively coded and analyzed with transition network analysis, sequence analysis and partial correlation networks as well…
How AI ‐Generated Feedback Hinders or Helps Learning
Delving into the psychology of Machines
Large language models (LLMs) offer the potential to simulate human-like responses and behaviors, creating new opportunities for psychological science. In the context of self-regulated learning (SRL), if LLMs can reliably simulate survey responses at scale and speed, they could be used to test intervention scenarios, refine theoretical models, augment sparse datasets, and represent hard-to-reach populations. However, the validity of LLM-generated …
A Topical Review of Research in Computer-Supported Collaborative Learning
This study maps the evolution and state of Computer-Supported Collaborative Learning (CSCL) research, analyzing 6388 documents published between 1990 and 2022. The findings highlight the sustained engagement of a core group of scholars and the field's geographic concentration in Western countries, particularly the USA and Europe. While the field remains productive and diverse, recent trends reflect a growing emphasis on integrating emerging techn…
Changes in online course designs
The switch to emergency remote teaching during the COVID-19 pandemic became for many university instructors a necessity to familiarise themselves with the institution’s online learning management system (LMS). This switch to online teaching made learning activities, course design patterns, and pedagogical approaches more visible than during face-to-face teaching. Furthermore, the process of translating physical learning activities to the digital …
Using learning analytics to understand student perceptions of peer feedback
Peer assessment (PA) is the process of students grading and giving feedback to each other's work. Learning analytics is a field focused on analysing educational data to understand and improve learning processes. Using learning analytics on PA data has the potential to gain new insights into the feedback giving/receiving process. This exploratory study focuses on backward evaluation, an under researched aspect of peer assessment, where students re…
Backward evaluation in peer assessment
Implementing backward evaluation as part of the peer assessment process enables students to react to the feedback they receive on their work within one peer assessment activity cycle. The emergence of online peer assessment platforms has brought new opportunities to study the peer assessment process, including backward evaluation, through the digital data that the use of these systems generates. This scoping review provides an overview of peer as…
No prominent works on this page.
Using learning analytics to understand student perceptions of peer feedback
Peer assessment (PA) is the process of students grading and giving feedback to each other's work. Learning analytics is a field focused on analysing educational data to understand and improve learning processes. Using learning analytics on PA data has the potential to gain new insights into the feedback giving/receiving process. This exploratory study focuses on backward evaluation, an under researched aspect of peer assessment, where students re…
Backward evaluation in peer assessment
Implementing backward evaluation as part of the peer assessment process enables students to react to the feedback they receive on their work within one peer assessment activity cycle. The emergence of online peer assessment platforms has brought new opportunities to study the peer assessment process, including backward evaluation, through the digital data that the use of these systems generates. This scoping review provides an overview of peer as…
Changes in online course designs
The switch to emergency remote teaching during the COVID-19 pandemic became for many university instructors a necessity to familiarise themselves with the institution’s online learning management system (LMS). This switch to online teaching made learning activities, course design patterns, and pedagogical approaches more visible than during face-to-face teaching. Furthermore, the process of translating physical learning activities to the digital …
Delving into the psychology of Machines
Large language models (LLMs) offer the potential to simulate human-like responses and behaviors, creating new opportunities for psychological science. In the context of self-regulated learning (SRL), if LLMs can reliably simulate survey responses at scale and speed, they could be used to test intervention scenarios, refine theoretical models, augment sparse datasets, and represent hard-to-reach populations. However, the validity of LLM-generated …
A Topical Review of Research in Computer-Supported Collaborative Learning
This study maps the evolution and state of Computer-Supported Collaborative Learning (CSCL) research, analyzing 6388 documents published between 1990 and 2022. The findings highlight the sustained engagement of a core group of scholars and the field's geographic concentration in Western countries, particularly the USA and Europe. While the field remains productive and diverse, recent trends reflect a growing emphasis on integrating emerging techn…
Do modes of presence matter? regulation and participation in graduate students’ hybrid synchronous group-based collaboration
STRUCTURED Abstract Background Synchronous hybrid education offers flexibility and accessibility, but can also pose challenges for students in regulating group work and ensuring equal participation in collaborative activities. Understanding how students address the challenges of regulation and participation in hybrid collaboration settings is critical for designing and supporting students for hybrid education. Aims This exploratory study examines…
Human-AI collaboration or obedient and often clueless AI in instruct, serve, repeat dynamics
While research on human-AI collaboration exists, it mainly examined language learning and used traditional counting methods with little attention to evolution and dynamics of collaboration on cognitively demanding tasks. This study examines human-AI interactions while solving a complex problem. Student-AI interactions were qualitatively coded and analyzed with transition network analysis, sequence analysis and partial correlation networks as well…
How AI ‐Generated Feedback Hinders or Helps Learning
Psychology (5 works) · Computer Science (4 works) · Mathematics education (4 works) · Innovative Teaching and Learning Methods (3 works) · Online Learning and Analytics (3 works) · Peer Assessment (2 works) · Student Assessment and Feedback (2 works) · Affordance (1 work) · AI in Service Interactions (1 work) · AI-based Problem Solving and Planning (1 work)