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Linking learning behavior analytics and learning science concepts: Designing a learning analytics dashboard for feedback to support learning regulation
Open accessAbstract
Abstract Technological advancements have generated a strong interest in exploring learner behavior data through learning analytics to provide both learner and instructor with process-oriented feedback in the form of dashboards. However, little is known about the typology of dashboard feedback relevant for different learning goals, learners and teachers. While most dashboards and the feedback that they give are based only on learner performance indicators, research shows that effective feedback needs also to be grounded in the regulatory mechanisms underlying learning processes and an awareness of the learner's learning goals. The design artefact presented in this article uses a conceptual model that visualizes the relationships between dashboard design and the learning sciences to provide cognitive and behavioral process-oriented feedback to learners and teachers to support regulation of learning. A practical case example is given that demonstrates how the ideas presented in the paper can be deployed in the context of a learning dashboard. The case example uses several analytics/visualization techniques based on empirical evidence from earlier research that successfully tested these techniques in various learning contexts.
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Written from the paper’s full text.
TL;DR
The paper proposes a conceptual model that links learning analytics dashboard (LAD) feedback to learning-science concepts—regulation of learning, feedback typology, goal orientation, and effectiveness/efficiency—to provide process-oriented cognitive and behavioral feedback to learners and teachers. It illustrates the model with dashboard case examples using visualization and process analytics, but does not empirically evaluate the model.
Key findings
- Most existing LADs rely on performance/outcome indicators and lack theoretical grounding in the learning sciences; the paper argues effective feedback must account for regulatory mechanisms, learning goals, and goal orientations (mastery, performance, approach/avoidance).
- The proposed model distinguishes cognitive feedback (corrective, epistemic, suggestive) from behavioral feedback, and links them to self-regulated and co-regulated learning phases: planning, monitoring, and adaptation.
- It recommends using task-specific subgoals (TSSGs), backward instructional design, resource/time utility, and effectiveness/efficiency indicators to determine feedback type and timing, and to complement statistical/data-mining approaches with process analytics.
- Case examples illustrate the model: a planning example requires 60% performance for topic C, four web lectures, two homework assignments, and expected time ≤5 hours; a monitoring example shows trial 5 result 80% vs required 90% (failed) with hints; an adaptation example reports result = 100%, 5 trials, 8 corrections, score = 10, ineffective time utility (3.5 h, 5.2 h, 0.5 h); a group example notes communication score 5/20 and initiative/attendance rated on average 10/20. These are illustrative, not empirical findings.
Methods
- Design Science in Information Systems research, using conceptual modeling; the paper focuses on the first two design-science principles: designing a purposeful artifact and establishing relevance.
- No new empirical sample or outcome study is reported; the conceptual model is derived from a review of LAD studies, feedback research, self-regulated/co-regulated learning, goal orientation, and effectiveness/efficiency concepts.
- Case examples use analytics/visualization techniques based on earlier empirical research; one group-interactivity example was piloted by analysis of data from the authors’ experiment at LeaForum using WeSpot activity logs.
Limitations
- Stated: implementation mechanisms (e.g., prototype design), evaluation, and expansion of the design are left as further research; the case examples are not exhaustive, do not provide technical implementation detail, and do not test which visualization techniques work better.
- Stated: detailed mechanisms for user intervention in feedback remain challenging.
- Evident: the conceptual model is not empirically validated in this paper; there is no participant sample, outcome measure, or formal evaluation of the proposed dashboard feedback.
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In the paper
“Common to all feedback LADs presented in the literature on dashboards is the lack of theoretical support grounded in the learning sciences (Sedrakyan, Järvelä & Kirschner, 2016) and research on feedback and underlying mechanisms of learning processes.”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 1. Introduction
What the sources say
- Not checked yetcites Sedrakyan, Järvelä & Kirschner, 2016
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIn the paper
“Research has shown that the sooner students receive feedback on what they have done, the more effective it is for their learning (Irons, 2008).”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 3.2.2.1. Timeliness of feedback
What the sources say
- Not checked yetcites Irons, 2008
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIn the paper
“Another issue with current tools is finding evidence for their formal validation, e.g.whether the tools fulfill their intended purpose, such as having a positive impact on learning; encouraging more efficient learning; or more effective learning (Ferguson et al., 2016), which suggests that LADs should consider built-in mechanisms to allow tracking effects from such interventions.”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 3.1. Earlier LAD Studies
What the sources say
- Not checked yetcites Ferguson et al., 2016
Load-bearingStrength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIn the paper
“Goal orientation has been found to affect learning behavior (Stevens & Gist, 1997).”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 3.2.2.3. Learning orientations and behaviors
What the sources say
- Not checked yetcites Stevens & Gist, 1997
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIn the paper
“In terms of the intended goals of dashboards, most studies limit themselves to student performance outcomes through self-reflection, awareness, and self-assessment (Bodily & Verbert, 2017) positioning learners in comparison with teacher specified and/or peer performance.”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 3.1. Earlier LAD Studies
What the sources say
- Not checked yetcites Bodily & Verbert, 2017
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIn the paper
“Research has shown that successful learners use a repertoire of strategies to guide and enhance their learning process cognitive, behavioral and motivationaltoward completing academic tasks (Zimmerman & Schunk, 2011).”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 3.2.1. Regulation of Learning
What the sources say
- Not checked yetcites Zimmerman & Schunk, 2011
Strength:boosted· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesNone of the sources cited for this claim have been checked yet.
In the paper
“For example, most current Learning Analytics Dashboards (LADs) are based only on learner performance indicators (e.g., where a learner is doing well/poor, how much content has been completed, how much time was spent, how learners' progress compares to teacher specified and/or peer scores) that do not seem to contribute to learners' motivation and engagement (Blumenfeld, 1992;Elliott & Harackiewicz”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 1. Introduction
What the sources say
- Not checked yetcites Blumenfeld, 1992 source
- Not checked yetcites Elliott & Harackiewicz, 1996
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesNone of the sources cited for this claim have been checked yet.
In the paper
“For example, most current Learning Analytics Dashboards (LADs) are based only on learner performance indicators (e.g., where a learner is doing well/poor, how much content has been completed, how much time was spent, how learners' progress compares to teacher specified and/or peer scores) that do not seem to contribute to learners' motivation and engagement (Blumenfeld, 1992;Elliott & Harackiewicz”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 1. Introduction
What the sources say
- Not checked yetcites Blumenfeld, 1992 source
- Not checked yetcites Elliott & Harackiewicz, 1996
Load-bearingStrength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIn the paper
“Furthermore, recent research on the effectiveness of learning analytics tools reveals that when using performance-oriented dashboards, learner mastery orientation decreases (Lonn, Aguilar, & Teasley, 2015).”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 1. Introduction
What the sources say
- Not checked yetcites Lonn, Aguilar, & Teasley, 2015
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIn the paper
“In terms of analysis approach in the context of LADs feedback, data mining approaches prevail targeting performance visualization and outcome feedback (”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 3.1. Earlier LAD Studies
What the sources say
- Not checked yetcites Sedrakyan, De Weerdt, & Snoeck, 2016
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
- Probably not a substantial claim. 46
- It may state two separate claims as one. 16
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“According to the goals, Group 6 shows a desired (e.g., balanced) interaction.”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 4.7.1. Feedback Perspectives with Respect to Detecting Group Learning Process Regulation Needs
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
- Rests on an assumption: Group dynamics and interactivity are to a large extent predictive for the collaborative nature of learning processes.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“For instance, if a teacher specified a balanced interactivity for a task in which a group member should contribute to active discussion on the analysis results, it is obvious from Figure 8 that in groups 1-5, there are some problems with collaboration because either not all participants are involved or some participants' activities are limited.”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 4.7.1. Feedback Perspectives with Respect to Detecting Group Learning Process Regulation Needs
Strength:boosted· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: Group dynamics and interactivity are to a large extent predictive for the collaborative nature of learning processes.
In the paper
“In the context of feedback research, these approaches translate into two major forms: explanations targeted at improving cognitive dimensions of knowledge (e.g., understanding) and guidance to influence a learner's behavior (e.g., engaging in a specific type of activity believed to be related to a successful learning path; Sedrakyan, 2016).”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 3.2.2.2. Typology of feedback
What the sources say
- Not checked yetcites Sedrakyan, 2016
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
In the paper
“According to Sawyer (2014), most research on educational dashboards lacks both theoretical support from recent advancements in the learning sciences and an evidenceinformed foundation for choosing the data that can assist in observing and assessing learning processes to identify the feedback needs of learners/teachers.”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 1. Introduction
What the sources say
- Not checked yetcites Sawyer (2014)
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“Although self-regulation concerns individual adaptation, feedback mechanisms that the environment or peers provide can also be considered as a form of co-regulated learning (Isohätälä, Järvenoja, & Järvelä, 2017).”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 3.2.1. Regulation of Learning
What the sources say
- Not checked yetcites Isohätälä, Järvenoja, & Järvelä, 2017
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“This type of feedback aims to improve learners' understanding of intermediate solutions allowing them to engage in self-regulatory learning mechanisms (van Merriënboer & Kirschner, 2012).”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 3.2.2.2. Typology of feedback
What the sources say
- Not checked yetcites van Merriënboer & Kirschner, 2012
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
None of the sources cited for this claim have been checked yet.
In the paper
“Furthermore, recent studies on the effectiveness of existing dashboards suggest that learner goal orientations (Lonn et al., 2015) and differences in achievement levels (Park & Jo, 2015) need to be carefully considered in the design of any intervention, as the resulting approaches and tools can affect students' interpretations of their data and subsequent academic success.”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 3.1. Earlier LAD Studies
What the sources say
- Not checked yetcites Lonn et al., 2015 source
- Not checked yetcites Park & Jo, 2015
Tests✓ Asserted: passes✗ Checkable: fails✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may be too vague to check against evidence.
In the paper
“In practice, self-regulated and strategic learning involves experimenting with, and learning about, effective strategies for regulating aspects of their own, peers', and groups' shared learning processes (Winne, Hadwin, & Perry, 2013), including planning, setting goals, organizing, monitoring, and adapting.”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 3.2.1. Regulation of Learning
What the sources say
- Not checked yetcites Winne, Hadwin, & Perry, 2013
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
In the paper
“Even though psychologists and educators are not in complete agreement, most agree that learning may be explained by a combination of two basic approaches: cognitive theories (i.e., cognitivism, which views the learning process as a step-by-step knowledge construction process) and behavioral theories (i.e., behaviorism, in which learning is defined as a change of the behavior of a learner by rein”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 3.2.2.2. Typology of feedback
What the sources say
- Not checked yetcites Tomic, 1993
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Co-regulated learning (CoRL) occurs when learners' regulatory activities are guided, supported, shaped, or constrained by others, such as peers or teachers, and the social system, including the learning environment (Hadwin, Järvelä & Miller, 2017).”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 3.2.1. Regulation of Learning
What the sources say
- Not checked yetcites Hadwin, Järvelä & Miller, 2017
Tests✓ Asserted: passes✗ Checkable: fails✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The design artefact presented in this article uses a conceptual model that visualizes the relationships between dashboard design and the learning sciences to provide cognitive and behavioral process-oriented feedback to learners and teachers to support regulation of learning.”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > Abstract
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
- Rests on an assumption: The conceptual model presented is a valid guide for designing LAD feedback to support regulation of learning.
In the paper
“The regulation of learning and performance is central to research on feedback (Butler & Winne, 1995).”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 3.2.1. Regulation of Learning
What the sources say
- Not checked yetcites Butler & Winne, 1995 source
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
In the paper
“Empirical studies show that behavioral change and improved performance were observed when supporting learners in the interpretation of visualizations (Sedrakyan, 2016).”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 1. Introduction
What the sources say
- Not checked yetcites Sedrakyan, 2016
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“This type of process can be referred to as a sequencing of cognitive and behavioral activities, suggesting that in terms of data analysis approaches, we also need to consider the role of process (sequence) analytics (Sedrakyan, 2016;Sedrakyan, Snoeck & De Weerdt, 2014) as opposed to the statistical and data-mining approaches currently widely applied in research on learning analytics.”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 3.2.2.2. Typology of feedback
What the sources say
- Not checked yetcites Sedrakyan, 2016
- Not checked yetcites Sedrakyan, Snoeck & De Weerdt, 2014
Load-bearingStrength:hedged· not yet calibratedTests✓ Asserted: passes✗ Checkable: fails✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may be too vague to check against evidence.
None of the sources cited for this claim have been checked yet.
In the paper
“The approach allowed exploring learning process patterns that associate themselves with better/worse learning outcomes, subsequently being used as guidelines to improve teaching (Sedrakyan, De Weerdt & Snoeck, 2016;Sedrakyan, 2016).”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 4.7. Case Example
What the sources say
- Not checked yetcites Sedrakyan, De Weerdt & Snoeck, 2016
- Not checked yetcites Sedrakyan, 2016
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These profiles can use learner behavior following viewing and monitoring activities to show approximations of adaptation effort.”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 4.3.3. Adaptation profile
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. The paper may give no reason why it holds.
In the paper
“Depending on the types of goals learners possess, learning outcomes will target different levels of knowledge, skills, competences, or simply task completion, which also determines how learners engage with the regulated learning process (Winne, Hadwin, & Perry, 2013).”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 3.2.2.3. Learning orientations and behaviors
What the sources say
- Not checked yetcites Winne, Hadwin, & Perry, 2013
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
In the paper
“In general, a planning profile includes activities such as a) planning the sub-goals to reach, b) selection of learning strategy (action plan), c) the materials and resources to use, and c) allocation of time (Pintrich, 2000).”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 4.3.1. Planning profile
What the sources say
- Not checked yetcites Pintrich, 2000 source
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A co-adaptation profile will utilize the concept of peer-oriented feedback (e.g., “Could you give feedback on your peer task results?”) both for individual and group learning plans.”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 4.3.3. Adaptation profile
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A self-monitoring profile can inform a learner about his or her progress with respect to an action plan and self-defined goals.”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 4.3.2. Monitoring profile
Tests✓ Asserted: passes✗ Checkable: fails✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These planning profiles will be used both to guide learners and inform teachers about the coherence and alignment between learners' and teacher's specified goals and action plans.”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 4.3.1. Planning profile
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“whereas a learner's attempt in combination with outcomes, utilized time and resources (as well as feedback received on earlier attempt) will allow measuring if the self-regulation effort was successful or sufficient.”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 4.2. How Can Typology of Feedback and Potential Intervention Time be
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Absence of another trial might for instance suggest a need for behavioral feedback to engage a learner in a regulatory process,”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 4.2. How Can Typology of Feedback and Potential Intervention Time be
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“That is, by creating visible artefacts of varying sub-goals related to mastering the new knowledge or skills and/or competence, we can make them observable in the learning process for both the instructor and learner.”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 4.1. How Can Learning Processes Be Measured with Respect to the Concepts of Regulation and Learning Goals?
Tests✓ Asserted: passes✗ Checkable: fails✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
In the paper
“Task-specific subgoals (TSSG) include steps that are a) specific, b) measurable, c) action-oriented, d) realistic, and e) temporal (Winne & Hadwin, 1998).”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 4.1. How Can Learning Processes Be Measured with Respect to the Concepts of Regulation and Learning Goals?
What the sources say
- Not checked yetcites Winne & Hadwin, 1998
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
In the paper
“Previous studies have identified important variables dealing with user acceptance for computer-assisted learning environments, such as the Technology Acceptance Model (Davis, 1989), which suggests ease of use and perceived usefulness as important factors contributing to the user acceptance (i.e., actual utility) of LAD feedback.”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 4.4. User Acceptance and Control over Feedback
What the sources say
- Not checked yetcites Davis, 1989 source
Strength:hedged· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“For example, “backward design,” which is a well-known instructional design model, uses goal setting as the focal point of lesson design (Wiggins & McTighe, 1998).”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 4.1. How Can Learning Processes Be Measured with Respect to the Concepts of Regulation and Learning Goals?
What the sources say
- Not checked yetcites Wiggins & McTighe, 1998
Strength:boosted· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The planning profiles can also provide additional information about the overall level of preparedness, preferences and difficulties of learners.”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 4.3.1. Planning profile
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For instance, an increased or decreased effort in combination with achievements (e.g., score) can be indicative of whether activities, such as attending classes, use of a learning resource, task completion, or received feedback had an impact on achievement.”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 4.3.3. Adaptation profile
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We posit that based on these goals, LADs should be able to propose personalized learning trajectories (action plans), also taking into consideration the level of preparedness and dependencies between learning (sub-)goals.”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 3.2.2.3. Learning orientations and behaviors
Tests✓ Asserted: passes✗ Checkable: fails✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may be too vague to check against evidence.
- Rests on an assumption: The learning science concepts reviewed (regulation of learning, feedback typology, goal orientation, efficiency and effectiveness) are the relevant and sufficient concepts for designing LAD feedback.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This model can serve as a general framework for designing and building information systems as a basis for educational dashboard feedback.”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 4.6. A Conceptual Design of LAD Feedback Based on Conceptual Review
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“we posit that the detection of inefficient processes can be useful in determining the timeliness (receive time) of the feedback.”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 4.2. How Can Typology of Feedback and Potential Intervention Time be
Strength:plain· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✗ Checkable: fails✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Adaptation profiles can inform learners about the level of effort put into learning regulation and the needs for adaptation (e.g., how learners perform with learning challenges, the resources they use, how much time they spend, and whether they need additional feedback).”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 4.3.3. Adaptation profile
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. The paper may give no reason why it holds.
In the paper
“Goal-directed behavior that results from self-goal setting is empowering and proactive, as students take responsibility and ownership (Elliot & Fryer, 2008).”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 3.2.2.3. Learning orientations and behaviors
What the sources say
- Not checked yetcites Elliot & Fryer, 2008
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“When using backward design, instructors identify learning goals for the course first, considering what they want students to know and be able to do when they finish the course, and then determine acceptable evidence regarding whether those goals are met and plan learning experiences and instruction to achieve those learning goals (Wiggins & McTighe, 1998).”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 4.1. How Can Learning Processes Be Measured with Respect to the Concepts of Regulation and Learning Goals?
What the sources say
- Not checked yetcites Wiggins & McTighe, 1998
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A self-adaptation profile will inform a learner about how successful he or she was in addressing a challenge and what actions he or she can take to address a detected challenge.”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 4.3.3. Adaptation profile
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In summary, by complementing the idea of feedback with the concepts of effectiveness and efficiency, it is possible to assess a learning progress with respect to potential intervention needs and, more specifically, with respect to determining optimal”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 3.2.2.4. Learning progress: Efficiency and effectiveness of learning processes
Tests✓ Asserted: passes? Checkable: unclear✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: The learning science concepts reviewed (regulation of learning, feedback typology, goal orientation, efficiency and effectiveness) are the relevant and sufficient concepts for designing LAD feedback.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In summary, while the outputs of TSSGs and engagement patterns will allow distinguishing the needs for the type of feedback (cognitive or behavioral), these also allow expanding dashboard performance visualizations with textual feedback to learners and teachers.”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 4.2. How Can Typology of Feedback and Potential Intervention Time be
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes? Based: unclearIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The model allows for the generation of process-oriented feedback to different users (e.g., teacher and learners) related to different learning goals.”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 4.6. A Conceptual Design of LAD Feedback Based on Conceptual Review
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In the planning phase, using backward design, the task specific sub-goals necessary to obtain a knowledge or skill are linked with mastering the proposed learning material.”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 4.3.1. Planning profile
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For example, if the expected utility of a specific resource within a meaningful (agreed) time does not lead to the achievement of the expected learning goal, either for a specific learner or group of learners (depending on the observation target), it might suggest that the resource for a specific goal contains a certain level of “difficulty” for that cluster, and vice versa.”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 4.2. How Can Typology of Feedback and Potential Intervention Time be
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“According to goal-setting theory, goals should be short term rather than long term and challenging (Latham & Locke, 2002) and “Specific, Measurable, Achievable, Relevant, Time-framed” (SMART; Drucker, 1954).”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 4.1. How Can Learning Processes Be Measured with Respect to the Concepts of Regulation and Learning Goals?
What the sources say
- Not checked yetcites Latham & Locke, 2002
- Not checked yetcites Drucker, 1954
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In general, the role of the monitoring profile in the context of dashboards is to detect and suggest further adaptation needs for learners and inform teachers about difficulties if the expected performance level is not being achieved within an agreed action plan and timeframe (see the case example for further details).”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 4.3.2. Monitoring profile
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These resources can serve as artefacts of instructor expectations or planning.”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 4.3.1. Planning profile
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A comonitoring profile can also provide information about how well a learner performs with respect to his or her peers if the goal orientation is set to “performance”.”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 4.3.2. Monitoring profile
Strength:plain· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The feedback idea presented in this example was piloted by the analysis of data from the authors' experiment conducted at LeaForum (http://www.oulu.fi/leaf-eng/).”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 4.7.1. Feedback Perspectives with Respect to Detecting Group Learning Process Regulation Needs
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Group standards can be used to provide group-oriented monitoring feedback (see the discussed theoretical concept in section 3.2.1,3.2.2 and the measurment and presentation layer concepts in sections 4.1 and 4.3).”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 4.7. Case Example
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✗ Checkable: fails✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Ultimately, the proposed design model allows extending dashboard feedback with textual explanations in the form of cognitive and behavioral feedback which makes learning-process data visualizations easier to interpret for an end user.”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > Group 4
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“as the case example makes use of visualization techniques based on empirical evidence from earlier research, investigating other visualization techniques and testing which techniques can work better in supporting the feedback ideas presented in this paper can yet be another possible future research direction.”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > Group 4
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Several researchers argue that showing an aggregated analysis with respect to peer performance is a good approach (Lonn et al., 2015).”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 4.7. Case Example
What the sources say
- Not checked yetcites Lonn et al., 2015 source
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Such feedback can be constructed based on learner profiles of regulation process phases spanning the planning, monitoring, and adapting activities thus allowing detecting inefficient processes in learning.”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > Group 4
Tests✓ Asserted: passes✗ Checkable: fails✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Further,”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > Group 4
Tests✓ Asserted: passes✗ Checkable: fails✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For instance, visual inspection can easily reveal if the interactions are balanced within a group or concentrated among particular members.”
§ Linking Learning Behavior Analytics and Learning Science Concepts: Designing a Learning Analytics Dashboard for Feedback to Support Learning Regulation > 4.7.1. Feedback Perspectives with Respect to Detecting Group Learning Process Regulation Needs
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
The paper relies on this without support.
The conceptual model presented is a valid guide for designing LAD feedback to support regulation of learning.
“The design artefact presented in this article uses a conceptual model that visualizes the relationships between dashboard design and the learning sciences to provide cognitive and behavioral process-oriented feedback to learners and teachers to support regulation of learning.”
“The model aims to address the gap between LADs and learning theories serving as both a basis for building information systems and thus also helping to understand future data needs, and an initial platform to guide future research in this domain.”
The paper relies on this without support.
The learning science concepts reviewed (regulation of learning, feedback typology, goal orientation, efficiency and effectiveness) are the relevant and sufficient concepts for designing LAD feedback.
“This section provides a preliminary discussion on what concepts we need to support in the design of dashboard feedback to make it possible to observe learning processes with respect to potential feedback (i.e., regulation in learning) needs of different learners for different learning goals.”
“In this work, we complement the engineering approach with theories in the learning sciences to design a novel artefact, namely, a process-oriented feedback model in the context of LADs.”
The authors state this as an assumption.
TSSGs are initially carefully defined by an instructor in the context of instruction design and in accordance with goal-setting theory.
“To enable dashboard feedback based on TSSGs, we create the premise that they are initially carefully defined by an instructor in the context of instruction design and in accordance with goal-setting theory.”
The authors state this as an assumption.
A teacher is responsible for ensuring the quality of a goal in terms of being SMART.
“In this paper, we assume that a teacher is responsible for ensuring the quality of a goal in terms of being SMART.”
The paper relies on this without support.
Goals provide learners with standards against which they can monitor the learning process and progress.
“From a self-regulated learning perspective, goals provide learners with standards against which they can monitor the learning process and progress.”
The paper relies on this without support.
Metacognitive monitoring enables learners to adjust or change their goals, plans, or strategies for learning.
“From a regulated learning point of view, metacognitive monitoring enables learners to adjust or change their goals, plans, or strategies for learning.”
The paper relies on this without support.
User acceptance can be an important factor affecting the successful use of dashboard feedback.
“Despite the intended benefits of dashboards, user acceptance can be yet another important factor affecting the successful use of dashboard feedback.”
The paper relies on this without support.
Monitoring can prove distracting and thereby alter the nature of learning in a negative way.
“During the learning process, monitoring can prove distracting and thereby alter the nature of learning in a negative way.”
The paper relies on this without support.
Too much feedback can be as harmful as delayed feedback.
“Too much feedback can be as harmful as delayed feedback.”
The paper relies on this without support.
Group dynamics and interactivity are to a large extent predictive for the collaborative nature of learning processes.
“The motivation for this choice is that group dynamics and interactivity are to a large extent predictive for the collaborative nature of learning processes.”
The paper relies on this without support.
Existing LAD solutions mainly focus on performance orientation.
“which is the main focus of existing solutions.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Since the emergence of the field of LA in 2011, several studies have explored the potential for LA to improve feedback practices (Misiejuk et al., 2021; Pardo, 2018; Sedrakyan et al., 2020).”
From A systematic review of the role of learning analytics in enhancing feedback practices in higher education (2022) · cites this paper as Sedrakyan et al., 2020
In the citing paper
“Sedrakyan et al. (2020) and Lim et al. ' s (2021) found that the use of LA-based feedback supported self-regulated learning”
From A systematic review of the role of learning analytics in enhancing feedback practices in higher education (2022) · cites this paper as Sedrakyan et al., 2020
In the citing paper
“while LA feedback for students is mostly focused on their own learning performance to provide personalized feedback and to help them with regulating their learning (e.g., Pardo et al., 2019; Sedrakyan et al., 2020).”
From A systematic review of the role of learning analytics in enhancing feedback practices in higher education (2022) · cites this paper as Sedrakyan et al., 2020
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Limits and Virtues of Educational Technology in Elementary School Mathematics
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Learning Analytics in the Era of Large Language Models
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Improving summary writing through formative feedback in a technology‐enhanced learning environment
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Measuring Students’ Self-Regulatory Phases in LMS with Behavior and Real-Time Self Report
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Self-citationArtificial Intelligence and Education
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Examining Teachers’ Perception on the Impact of Positive Feedback on School Students
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The Sequence Matters in Learning - A Systematic Literature Review
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Designing Theory-Driven Analytics-Enhanced Self-Regulated Learning Applications
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Metadata
- Authors
- Sedrakyan, G., Malmberg, J., Verbert, K., Järvelä, S., & Kirschner, P. A.
- Affiliations
- Ghent University (BE)
- University of Oulu (FI)
- KU Leuven (BE)
- Open University of the Netherlands (NL)
- Corresponding author
- Sedrakyan, Gayane
- Venue
- Computers in Human Behavior
- Publisher
- Elsevier BV
- Published
- 2020-06
- Volume
- 107
- Pages
- 105512
- ISSN
- 0747-5632 (ISSN-L)
- OpenAlex
- W2800204907
- Semantic Scholar
- 8b54eae687cf4632a0a6da7ac0fbd0ffca5540b9
- Cited by
- 283
- References
- 93
- Citations by year
- 2026: 21 · 2025: 33 · 2024: 45 · 2023: 49 · 2022: 44 · 2021: 42 · 2020: 26
- FWCI
- 27.79
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Computers in Human Behavior (publishedVersion)
- Lirias (KU Leuven) (acceptedVersion, other-oa)
- DSpace (Open University in the Netherlands) (submittedVersion, public-domain)
- DSpace (Open University in the Netherlands) (submittedVersion, other-oa)
- Funders
- Belgian Scientific Organization (V4.533.15N)
- Internal Funds of KU Leuven - PROFEELEARN (PDM/16/044)
- JUMO
- Academy of Finland
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › Data Visualization and Analytics
- Keywords
- learning analytics dashboards, learning regulation, process-oriented feedback, learning objectives, student self-regulation, dashboard design, conceptual model, visualization techniques, instructor feedback
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-10-10, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-10 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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