Connecting Learning Analytics and Problem-Based Learning – Potentials and Challenges

Kilińska, Daria; Ryberg, Thomas

doi:10.5278/ojs.jpblhe.v7i1.2545

Cited by 5 publications

(7 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The popularity of online learning, the challenge of extracting value from educational big data, and the demand to improve performance are the three driving forces in the emergence of LA (Ferguson, 2012). The data used in LA are mainly gathered through monitoring students' activity in online learning platforms (e.g., access to resources, logins, textual input) and materials from other various tools, techniques, or environments (e.g., forums, blogs, interactive whiteboards, social sites, and libraries) (Kilinska and Ryberg, 2019). LA methods are based on educational data mining, which includes relationship mining, prediction, modeling the user's knowledge domain, personalization and adaption, and structure discovery and analysis, as well as traditional evaluation and monitoring (Siemens, 10.3389/fpsyg.2023.1080294 Frontiers in Psychology 03 frontiersin.org 2013).…”

Section: Learning Analyticsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

“…Researchers summarize four key elements of PBL: the design of ill-structured learning problems, the role of the instructor as a facilitator, students’ self-regulation in the learning process, and peer learning to interact with others ( Savery, 2006 ; Kilinska and Ryberg, 2019 ). The notion of ill-structured problems as the driving force for learning is a very central aspect of PBL ( Kilinska and Ryberg, 2019 ). As opposed to presenting direct facts and conventional concepts in traditional instruction, complicated real-world problems are used in PBL to improve and promote student learning ( Joshi et al, 2020 ).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Problem-based learning (PBL) is a pedagogical philosophy covering a multitude of practices and has been employed in different institutes and diverse domains in the last 50 years ( Kilinska and Ryberg, 2019 ). PBL aims to educate students through the process of solving problems ( Neville, 2009 ).…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Key factors predicting problem-based learning in online environments: Evidence from multimodal learning analytics

Wang

Sun²,

Luo³

2023

Front. Psychol.

View full text Add to dashboard Cite

Problem-based learning (PBL) has been used in different domains, and there is overwhelming evidence of its value. As an emerging field with excellent prospects, learning analytics (LA)—especially multimodal learning analytics (MMLA)—has increasingly attracted the attention of researchers in PBL. However, current research on the integration of LA with PBL has not related LA results with specific PBL steps or paid enough attention to the interaction in peer learning, especially for text data generated from peer interaction. This study employed MMLA based on machine learning (ML) to quantify the process engagement of peer learning, identify log behaviors, self-regulation, and other factors, and then predict online PBL performance. Participants were 104 fourth-year students in an online course on social work and problem-solving. The MMLA model contained multimodal data from online discussions, log files, reports, and questionnaires. ML classification models were built to classify text data in online discussions. The results showed that self-regulation, messages post, message words, and peer learning engagement in representation, solution, and evaluation were predictive of online PBL performance. Hierarchical linear regression analyses indicated stronger predictive validity of the process indicators on online PBL performance than other indicators. This study addressed the scarcity of students’ process data and the inefficiency of analyzing text data, as well as providing information on targeted learning strategies to scaffold students in online PBL.

show abstract

Section: Learning Analyticsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Key factors predicting problem-based learning in online environments: Evidence from multimodal learning analytics

Wang

Sun²,

Luo³

2023

Front. Psychol.

View full text Add to dashboard Cite

show abstract

“…As an emerging field, EDM focuses on developing effective methods to analyze different types of data in educational environments, which can be used to better understand learners and their learning environments, so as to promote instruction and learning [37]. EDM mainly uses data from learners' activities in the digital learning environment such as resource access, log-in, and text input, as well as materials from various other tools, technologies, or environments, such as forums, blogs, interactive whiteboards, social networking sites, and libraries [38]. Many researchers believe that EDM can accumulate a significant amount of data, and enable stakeholders to understand the learning process, identify learners' knowledge and skills, find learners' weaknesses and confusion, evaluate the efficiency of learning, and ultimately improve learning [39].…”

Section: Educational Data Miningmentioning

confidence: 99%

Sustainable Development of Emergency Response Ability of Novice Policemen—An Empirical Study Based on Case-Based Instruction

et al. 2023

View full text Add to dashboard Cite

The emergency response ability of police officers is a critical component of their career, and is also an important support for public security. However, few researchers have focused on the factors that influence emergency response ability, especially in the group of novice policemen. On the other hand, as the popular way to train emergency response ability, case-based instruction (CBI) generates various types of data, especially valuable text data; however, such text data is always ignored because of the lack of effective analysis methods. Therefore, this study employed automatic semantic analysis and hierarchical linear regression models to investigate the factors influencing the emergency response ability of novice policemen in the process of CBI. Results indicated that, among personal differences, prior knowledge, and basic professional skills, the latter showed stronger predictive validity than the others. In particular, information processing and judgment, command and decision, and order maintenance were the main indicators. This study also illustrated that automatic semantic analysis can effectively identify deep value from semantic data, which will support stakeholders to design strategies, make decisions, conduct evaluations in training and instructions, and ultimately help sustainable development in human careers.

show abstract

Learning analytics dashboards are increasingly becoming about learning and not just analytics - A systematic review

Paulsen,

Lindsay

2024

Educ Inf Technol

View full text Add to dashboard Cite

This systematic review explores the emerging themes in the design and implementation of student-facing learning analytics dashboards in higher education. Learning Analytics has long been criticised for focusing too much on the analytics, and not enough on the learning. The review is then guided by an interest in whether these dashboards are still primarily analytics-driven or if they have become pedagogically informed over time. By mapping the identified themes of technological maturity, informing frameworks, affordances, data sources, and analytical levels over publications per year, the review identifies an emerging trajectory towards student-focused dashboards. These dashboards are informed by theory-oriented frameworks, designed to incorporate affordances that supporting student learning, and realised through integration of more than just activity data from learning management systems – allowing the dashboards to better support students' learnings processes. Based on this emerging trajectory, the review provides a series of design recommendations for student-focused dashboards that are connected to learning sciences as well as analytics.

show abstract

Connecting Learning Analytics and Problem-Based Learning – Potentials and Challenges

Cited by 5 publications

References 21 publications

Key factors predicting problem-based learning in online environments: Evidence from multimodal learning analytics

Key factors predicting problem-based learning in online environments: Evidence from multimodal learning analytics

Sustainable Development of Emergency Response Ability of Novice Policemen—An Empirical Study Based on Case-Based Instruction

Learning analytics dashboards are increasingly becoming about learning and not just analytics - A systematic review

Contact Info

Product

Resources

About