A systematic review of the role of learning analytics in enhancing feedback practices in higher education
Open accessAbstract
Learning analytics (LA) offers new opportunities to enrich feedback practices in higher education, but little is understood about the ways different LA can enhance feedback practices for educators and students. This systematic literature review maps the current state of implementation of LA to improve feedback practices in technology-mediated learning environments in higher education. We used strict inclusion criteria to select relevant studies that have investigated the role of LA on feedback practices. To identify common features of LA for feedback studies, we coded relevant publications using an analytical framework that identifies four key dimensions of LA systems: what (types of data), how (analytic methods), why (objectives), and how educators and students are served by LA (stakeholders). Based on findings, we propose a conceptual framework that can guide the implementation of LA for feedback systems and also suggest future empirical research in this area.
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TL;DR
This systematic review maps 46 empirical studies on learning analytics (LA) for feedback in higher education using Chatti et al.’s what/how/why/who framework. It proposes an evidence-based conceptual framework in which stakeholder and objective should guide data collection and analytic method choices for LA-based feedback.
Key findings
- LA feedback objectives most often targeted reflection (20 studies, 43%), personalization (13, 28%), prediction (11, 24%), assessment (11, 24%), adaptation (10, 22%), recommendation (10, 22%), and monitoring (6, 13%).
- LA-supported feedback was linked to pedagogical outcomes including academic performance (17, 37%), engagement/community of inquiry (11, 24%), self-regulation (8, 17%), motivation/emotion (8, 17%), time management (3, 6%), perception of feedback (2, 4%), cognitive load (2, 4%), reduced procrastination (1, 2%), satisfaction (1, 2%), reflective thinking (1, 2%), and transactional distance (1, 2%).
- Trace data was the dominant data type (23 codes, 36%), followed by assessment data (12, 18%), academic history data (11, 17%), and survey data (8, 12%); information visualization was the most common method (22 codes, 50%), then data mining (11, 25%), text analysis (8, 18%), and social network analysis (3, 7%).
- Students were stakeholders in all included publications, while educators were mentioned in 15 of 46; the proposed framework orders decisions as stakeholder → objective → data → method, with analytics levels (descriptive, diagnostic, predictive, prescriptive) tied to different feedback services.
Methods
- PRISMA systematic review; searched Web of Science, Scopus, ERIC, IEEE, and LAK proceedings with terms (“learning analytics” OR analytic* OR “data mining”) AND (feedback OR feedforward OR “formative assessment”); inclusion required English, 2011–2022, peer-reviewed journal articles, empirical studies, and higher education settings.
- From 1,318 initial records, after removing duplicates/non-peer-reviewed and screening, 46 studies met criteria and passed quality appraisal using Theelen et al. (2019) criteria; all 46 met the minimum methodology score.
- Publications were coded in ATLAS.ti 9 using a four-category scheme (what/how/why/who); inter-rater reliability on two randomly selected papers was 91% agreement (κ = 0.84, p < .001).
Limitations
- Stated: limited to empirical studies, so relevant reviews/conceptual papers may be missed; selected databases may miss unindexed studies; publication bias likely; findings are not generalizable to K-12; the review did not identify gaps in feedback features/purposes or investigate effect sizes of different data types.
- Stated: no distinction was made between educator feedback and peer feedback, and no analysis of how LA may affect affective, cognitive, and constructive features of feedback quality.
- Evident from the text: the coding scheme in Table 3 assigns the same code “C5” to both Personalization and Recommendation, and some table reference lists appear truncated or misaligned; these presentation issues may affect transparency of coding/reporting.
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- Findingown data§ 4.1. RQ1: for what reasons is LA used in feedback studies in higher education? · p. 8
Prediction (11 studies, 24%).
“Prediction | 11 | 24% |”
Quote in the paperNot a substantial claim - Findingown data§ 4.1. RQ1: for what reasons is LA used in feedback studies in higher education? · p. 8
Self-regulation in 8 studies (17%).
“Self-regulation | 8 | 17% |”
Quote in the paperNot a substantial claim - Findingown data§ 4.1. RQ1: for what reasons is LA used in feedback studies in higher education? · p. 8
Assessment (11 studies, 24%).
“Assessment | 11 | 24% |”
Quote in the paperNot a substantial claim - Findingreasoning§ 4.2.1. Data used for LA feedback intervention · p. 11
Trace data was the dominant data type used by LA to support feedback in higher education.
“Trace data : According to the reviewed studies, this is the dominant data type used by LA to support feedback in higher education.”
Quote in the paperNot a substantial claim - Findingown data§ 4.2. RQ2: what types of data does LA use to support feedback in higher education? · p. 11
Assessment data accounted for 12 codes (18%) in the review.
“12 | 18%”
Quote in the paperNot a substantial claim
- Findingown data§ 4.1. RQ1: for what reasons is LA used in feedback studies in higher education? · p. 8
Monitoring (6 studies, 13%).
“Monitoring | 6 | 13% |”
Quote in the paperNot a substantial claim - Findingown data§ 3.3. Identification of relevant publications · p. 4
The final pool for quality appraisal was 46 studies.
“leaving a final pool of only 46 studies for quality appraisal.”
- Also stated in: § 3.5. Included publications · p. 5 · plain
“Our final pool of 46 selected publications for final analysis is detailed in Table 2.”
Quote in the paperNot a substantial claim - Also stated in: § 3.5. Included publications · p. 5 · plain
- Findingown data§ 4.1. RQ1: for what reasons is LA used in feedback studies in higher education? · p. 8
Cognitive load in 2 studies (4%).
“Cognitive load | 2 | 4% |”
Quote in the paperNot a substantial claim - Findingown data§ 4.2. RQ2: what types of data does LA use to support feedback in higher education? · p. 10
The review identified 65 codes for types of data used by LA to support feedback in higher education.
“We identified 65 codes from the included publications based on our coding scheme that describing types of data used by LA to support feedback in higher education.”
Quote in the paperNot a substantial claim - Findingown data§ 4.1. RQ1: for what reasons is LA used in feedback studies in higher education? · p. 8
Personalization (13 studies, 28%).
“Personalization | 13 | 28% |”
Quote in the paperNot a substantial claim - Findingown data§ 4.2. RQ2: what types of data does LA use to support feedback in higher education? · p. 11
Trace data accounted for 23 codes (36%) in the review.
“codes 23 | 36%”
Quote in the paperNot a substantial claim - Findingown data§ 4.1. RQ1: for what reasons is LA used in feedback studies in higher education? · p. 8
Perception of feedback in 2 studies (4%).
“Perception of feedback | 2 | 4% |”
Quote in the paperNot a substantial claim - Findingown data§ 4.1. RQ1: for what reasons is LA used in feedback studies in higher education? · p. 8
The objectives for LA in feedback studies included Reflection (20 studies, 43%).
“Reflection | 20 | 43% |”
Quote in the paperSubstantial claim - Findingown data§ 4.1. RQ1: for what reasons is LA used in feedback studies in higher education? · p. 8
Adaptation (10 studies, 22%).
“Adaptation | 10 | 22% |”
Quote in the paperNot a substantial claim - Findingown data§ 4.1. RQ1: for what reasons is LA used in feedback studies in higher education? · p. 8
Motivation and emotion in 8 studies (17%).
“Motivation and emotion | 8 | 17% |”
Quote in the paperNot a substantial claim - Findingown data§ 4.1. RQ1: for what reasons is LA used in feedback studies in higher education? · p. 8
Time management in 3 studies (6%).
“Time management | 3 | 6% |”
Quote in the paperNot a substantial claim - Findingown data§ 4.2. RQ2: what types of data does LA use to support feedback in higher education? · p. 10
The identified data types were grouped into six main groups: trace data, assessment data, academic history data, demographic data, survey data, and interview data.
“we followed a bottom-up inductive approach to group data into six main groups: including trace data, assessment data, academic history data, demographic data, survey data, and interview data.”
Quote in the paperNot a substantial claim - Findingown data§ 4.1. RQ1: for what reasons is LA used in feedback studies in higher education? · p. 8
Engagement and community of inquiry in 11 studies (24%).
“Engagement and community of inquiry | 11 | 24% |”
Quote in the paperNot a substantial claim - Findingcitation§ 4.2.2. Data used for researching LA feedback intervention · p. 12
Interview data is used by LA for exploring student experiences, preferences, and perceptions of feedback.
“In feedback studies, interview data is used by LA for different reasons such as exploring student experiences, preferences, and perceptions of feedback (Conijn et al., 2020; Hunt et al., 2021; Lewis et al., 2021; Misiejuk et al., 2021).”
Quote in the paperNot a substantial claim0 of 3 sources checked - Findingcitation§ 4.1.2. Pedagogical objectives achieved through LA-supported feedback practices · p. 9
LA-supported feedback can help improve students' self-regulation skills.
“LA-supported feedback can also help with improving students ' self-regulation skills (e.g., Afzaal et al., 2021; Lim, Gasevic, et al., 2021).”
Quote in the paperSubstantial claim - Findingcitation§ 4.1.2. Pedagogical objectives achieved through LA-supported feedback practices · p. 10
There is a correlation between students' self-efficacy and LA-based feedback.
“Analysis of the reviewed papers also has shown that there is a correlation between students ' self-efficacy and LA-based feedback.”
Quote in the paperNot a substantial claim - Findingreasoning§ 4.2.1. Data used for LA feedback intervention · p. 12
Academic history data has little to say by itself in LA feedback studies.
“Similar to demographic data, this data type has also little to say by itself.”
Quote in the paperNot a substantial claim - Findingreasoning§ 4.2.1. Data used for LA feedback intervention · p. 12
In most current LA projects, demographic data is used alongside other data types for better interpretations.
“In current most of LA projects, demographic data is used alongside other data types for better interpretations of the data.”
Quote in the paperNot a substantial claim - Findingcitation§ 4.1.2. Pedagogical objectives achieved through LA-supported feedback practices · p. 10
Insights provided by LA methods, particularly ENA, can help educators understand how students perceive feedback.
“Insights provided by LA methods particularly Epistemic Network Analysis (ENA) can help educators to understand how students perceive feedback (Lim et al., 2020; Misiejuk et al., 2021).”
Quote in the paperNot a substantial claim - Findingcitation§ 4.1.2. Pedagogical objectives achieved through LA-supported feedback practices · p. 10
LA-based feedback can reduce students' procrastination.
“It was revealed that LA-based feedback can reduce students ' procrastination (Lim et al., 2020).”
Quote in the paperNot a substantial claim - Findingown data§ discussed below. · p. 13
Information visualization approach was used in 34 studies.
“We discovered that an information visualization approach was used is used in 34 studies (e.g. Lim et al., 2020; Yu et al., 2018).”
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- cites Yu et al., 2018
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- Findingcitation§ 4.1.2. Pedagogical objectives achieved through LA-supported feedback practices · p. 10
LA can be used to understand students' perceptions of feedback.
“In addition, LA can be used to understand students ' perceptions of feedback (Misiejuk et al., 2021).”
Quote in the paperNot a substantial claim - Findingown data§ discussed below. · p. 13
Information visualization alongside data mining methods were the most commonly used LA methods in the selected group of LA feedback studies.
“Information visualization alongside data mining methods were the most commonly used LA methods in our selected group of LA feedback studies.”
Quote in the paperNot a substantial claim - Findingcitation§ 4.1.2. Pedagogical objectives achieved through LA-supported feedback practices · p. 10
LA-based feedback influences students' cognitive load.
“We also found that LA-based feedback influences students ' cognitive load (Sun et al., 2019).”
Quote in the paperNot a substantial claim - Findingcitation§ 4.1.2. Pedagogical objectives achieved through LA-supported feedback practices · p. 10
LA-based feedback has the potential to save time for educators.
“LA-based feedback has shown the potential to save time for educators (Iraj et al., 2020; Shibani et al., 2020).”
Quote in the paperNot a substantial claim - Findingcitation§ 4.1.2. Pedagogical objectives achieved through LA-supported feedback practices · p. 9
When feedback practices are enhanced by LA insights, students' academic performance has also been improved.
“In a considerable number of reviewed studies (e.g., Karaoglan Yilmaz, 2022; Kohnke et al., 2022) we found that when feedback practices are enhanced by LA insights, students ' academic performance has also been improved.”
Quote in the paperSubstantial claim - Findingcitation§ 4.2.2. Data used for researching LA feedback intervention · p. 12
Interview data is used for providing personalized, predictive, reflective, adaptive, and recommendation feedback.
“Reviewed publications indicate that this kind of data is used for providing personalized, predictive, reflective, adaptive, and recommendation feedback (Conijn et al., 2020; Hunt et al., 2021; Lewis et al., 2021; Lim, Dawson, et al., 2021).”
Quote in the paperNot a substantial claim0 of 3 sources checked - Findingown data§ 4.3. RQ3: what methods does LA use to support feedback in higher education? · p. 12
In the pool of 46 published studies, 44 codes representing LA methods were identified.
“In our pool of 46 published studies, we identified 44 codes representing 'LA methods ' (Table 7).”
Quote in the paperNot a substantial claim - Findingreasoning§ 4.1.2. Pedagogical objectives achieved through LA-supported feedback practices · p. 10
LA-based feedback can increase students' satisfaction with feedback.
“In addition, LA-based feedback can increase students ' satisfaction with feedback (Pardo et al., 2019).”
Quote in the paperNot a substantial claim - Findingcitation§ 4.2.1. Data used for LA feedback intervention · p. 12
Assessment data mostly serve educators with evidence-based formative and summative assessment.
“Our review suggests that assessment data mostly serve educators with evidence-based formative and summative assessment (e.g. Choi & Cho, 2020; Tempelaar et al., 2015).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Choi & Cho, 2020
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- cites Tempelaar et al., 2015 source
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- Findingnone given§ 4.2.2. Data used for researching LA feedback intervention · p. 12
Survey data mostly is used for statistically exploring relationships among variables.
“our review suggests that survey data mostly is used for statistically exploring the relationships among variables.”
Quote in the paperNot a substantial claim - Findingcitation§ 4.1.1. LA objectives for enhancing feedback practices in higher education · p. 9
In the reviewed studies, LA allowed the delivery of personalized feedback at scale to each student in a large class.
“In other studies, LA allowed the delivery of personalized feedback at scale, to each student in a large class (Lewis et al., 2021; Lim, Gentili, et al., 2021; Pardo et al., 2019).”
Quote in the paperNot a substantial claim - Findingcitation§ 4.1.1. LA objectives for enhancing feedback practices in higher education · p. 9
In the reviewed studies, LA was used to support self-assessment or peer assessment.
“In others, LA was used to support self-assessment (e.g. Lim et al., 2020; Lim, Gasevic, et al., 2021; Shibani et al., 2020), or peer assessment (Misiejuk et al., 2021; Smith, 2020).”
Quote in the paperNot a substantial claim - Findingcitation§ 4.2.1. Data used for LA feedback intervention · p. 12
Demographic data have little to say solely by themselves.
“Although demographic data is very common to use in LA, they have little to say solely by themselves”
Quote in the paperNot a substantial claim - Findingcitation§ 4.4. RQ4: how does LA support feedback stakeholders in higher education? · p. 14
LA-based feedback helps educators with formative and summative assessment of students.
“helps educators with a formative and summative assessment of students (e.g. Chaudy & Connolly, 2019)”
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- Findingreasoning§ 4.4. RQ4: how does LA support feedback stakeholders in higher education? · p. 15
At the diagnostic level, LA-based feedback serves educators with monitoring students' activities and assessing them by spotlighting anomalies, similarities, and differences.
“at the diagnostic level, LA-based feedback serves educators with monitoring students ' activities and assessing them by spotlighting the anomalies, similarities, and differences in their learning activities.”
Quote in the paperNot a substantial claim - Findingcitation§ 4.4. RQ4: how does LA support feedback stakeholders in higher education? · p. 14
LA-based feedback provides assistance with monitoring students learning activities and progress for educators.
“For educators, LAbased feedback provides assistance with monitoring students learning activities and progress (e.g. Cornide-Reyes et al., 2020)”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Cornide-Reyes et al., 2020 source
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- Findingcitation§ 5. Discussion · p. 15
The four core elements of LA system development as outlined by Chatti et al. (2012) can guide systems that seek to draw on LA to deliver more effective provision of feedback.
“Our review confirmed that the four core elements of LA system development as outlined hypothetically by Chatti et al. (2012) can guide systems that seek to draw on LA to deliver the more effective provision of feedback.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Chatti et al. (2012) source
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- Findingcitation§ 4.4. RQ4: how does LA support feedback stakeholders in higher education? · p. 15
LA services increase students' motivation for learning engagement.
“increase their motivation for learning engagement (e.g. Lewis et al., 2021; Sun et al., 2019)”
Quote in the paperNot a substantial claim0 of 2 sources checked - Findingcitation§ 4.4. RQ4: how does LA support feedback stakeholders in higher education? · p. 14
Feedback based on LA provides students with personalized feedback given their learning activities.
“provides them with personalized feedback given their learning activities (e.g. Pardo et al., 2019)”
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- Findingcitation§ 4.4. RQ4: how does LA support feedback stakeholders in higher education? · p. 14
LA-based feedback helps educators to receive recommendations through automatic feedback for better pedagogical interventions.
“the use of LA for feedback helps educators to receive recommendations through automatic feedback for better pedagogical interventions (e.g. Azcona et al., 2019; Sedrakyan et al., 2016).”
Quote in the paperSubstantial claim0 of 2 sources checked - Findingcitation§ 4.4. RQ4: how does LA support feedback stakeholders in higher education? · p. 14
Based on self-observations, students are able to adjust and adapt their learning process in accordance with their learning needs.
“based on these self-observations they are able to adjust and adapt their learning process in accordance with their learning needs (e.g. Gibson et al., 2017).”
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- Findingown data§ discussed below. · p. 13
Most studies originally coded as 'other methods' actually made use of text analysis.
“Most of the studies whose method we originally coded as ' other methods ' (B5) using our coding scheme (Table 3) actually made use of text analysis.”
Quote in the paperNot a substantial claim - Findingown data§ discussed below. · p. 14
SNA was only used in five LA feedback studies.
“We found that SNA was only used in five LA feedback studies (Choi & Cho, 2020; Iandoli et al., 2014; Lim et al., 2020, 2021c; Misiejuk et al., 2021), though with various goals.”
Quote in the paperNot a substantial claim0 of 3 sources checked - Findingcitation§ 4.4. RQ4: how does LA support feedback stakeholders in higher education? · p. 14
LA-supported feedback provides a wider range of services compared to educators.
“For students, LA-supported feedback provides a wider range of services compared to educators.”
Quote in the paperSubstantial claim - Findingcitation§ discussed below. · p. 14
Our review revealed that text analytics methods were used for mining similarities and differences among students feedback, emotions, and perceptions.
“Our review revealed that text analytics methods were used for mining similarities, and differences among students feedback, emotions, and perceptions (Lee & Lim. 2016; Lim et al., 2020; Misiejuk et al., 2021).”
Quote in the paperNot a substantial claim0 of 3 sources checked - Findingcitation§ 4.4. RQ4: how does LA support feedback stakeholders in higher education? · p. 15
LA-based feedback provides weekly reports on students learning activities and progress.
“LA-based feedback provides weekly reports on students learning activities and progress (e.g. Tempelaar et al., 2018)”
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- Findingcitation§ 4.4. RQ4: how does LA support feedback stakeholders in higher education? · p. 14
Feedback based on LA informs students how they are doing.
“Reviewed studies showed that feedback based on LA informs students how they are doing (e.g. Hunt et al., 2021)”
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- Findingcitation§ 4.4. RQ4: how does LA support feedback stakeholders in higher education? · p. 15
LA services can result in less transactional distance in online learning environments.
“can result in the less transactional distance in online learning environments (e.g. Yilmaz & Yilmaz, 2020).”
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- Findingcitation§ 4.4. RQ4: how does LA support feedback stakeholders in higher education? · p. 15
LA-based feedback services encourage students to trust more in their confidence and self-efficacy.
“mentioned LA-based feedback services not only encourage students to trust more in their confidence and self-efficacy (e.g. Tsai et al., 2021)”
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- Findingown data§ discussed below. · p. 13
Predictive modeling (N=8) and clustering (N=6) were the most commonly used data mining methods.
“Of these, predictive modeling (N = 8) and clustering (N = 6) were the most commonly used.”
Quote in the paperNot a substantial claim - Findingcitation§ 4.4. RQ4: how does LA support feedback stakeholders in higher education? · p. 14
LA-based feedback supports educators with predictive feedback where educators can be early warned about students at risk of failure.
“supports educators with predictive feedback where educators can be early warned about students at risk of failure (e.g. Arnold & Pistilli, 2012).”
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- Findingcitation§ 4.4. RQ4: how does LA support feedback stakeholders in higher education? · p. 14
Feedback based on LA is positively correlated with educators' time management strategies and satisfaction.
“Selected studies also suggested that feedback based on LA is positively correlated with educators ' time management strategies and satisfaction (e.g. Iraj et al., 2020; Pardo et al., 2019; Shibani et al., 2020).”
Quote in the paperNot a substantial claim0 of 3 sources checked - Findingown data§ 5. Discussion · p. 15
LA for feedback projects most commonly drew on learning data.
“Our review revealed that while data usage varied, LA for feedback projects most commonly drew on learning data”
Quote in the paperSubstantial claim - Findingreasoning§ 5. Discussion · p. 15
Even where educators were identified as stakeholders, the ultimate goals are almost exclusively student-focused.
“Even where educators were identified as stakeholders of LA-based feedback systems, the ultimate goals are almost exclusively student-focused.”
Quote in the paperSubstantial claim - Findingreasoning§ 6. A conceptual framework to guide the use of LA for feedback practices in higher education · p. 15
The feedback services that LA provides for educators are different than the feedback services for students.
“The feedback services that LA provides for ed ucators are different than the feedback services for students.”
Quote in the paperSubstantial claim - Findingown data§ 5. Discussion · p. 15
Most projects sought to collect data more about the student learning process, rather than about educators or the teaching process.
“confirming that most projects sought to collect data more about the student learning process, rather than about educators, or the teaching process.”
Quote in the paperNot a substantial claim - Findingown data§ 5. Discussion · p. 15
Data mining methods were the most commonly employed in LA-based feedback systems.
“We found that different LA methods were employed in the selected feedback studies, however, data mining methods were the most commonly employed in LA-based feedback systems.”
Quote in the paperNot a substantial claim - Findingown data§ 5. Discussion · p. 15
LA has served educators and students in different ways at different levels.
“Finally, our analysis showed that LA has served educators and students in different ways at different levels.”
Quote in the paperSubstantial claim - Premisecitation§ Educational Research Review · p. 2
In online learning environments or with learning technologies, learning analytics offer the potential for provision of personalized, real-time, and relevant feedback at scale.
“Where learners are engaged in online learning environments, however, or making regular use of learning technologies, learning analytics (LA) offer the potential for provision of personalized, real-time, and relevant feedback at scale (Er et al., 2021; Pardo et al., 2019; Ryan et al., 2019; Lim et al., 2021).”
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- Premisecitation§ Educational Research Review · p. 2
Several studies have explored the potential for LA to improve feedback practices since the emergence of the field in 2011.
“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).”
Quote in the paperNot a substantial claim0 of 3 sources checked - Premisecitation§ 1.3. Learning analytics and feedback · p. 3
Existing literature reveals that LA can offer significant practical support for feedback practices.
“In summary, existing literature reveals that LA can offer significant practical support for feedback practices (e.g. Er et al., 2021; Lim, Gasevic, et al., 2021; Misiejuk et al., 2021)”
Quote in the paperSubstantial claim0 of 3 sources checked- cites Er et al., 2021
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- cites Lim, Gasevic, et al., 2021
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- cites Misiejuk et al., 2021 source
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- Premisecitation§ 1.3. Learning analytics and feedback · p. 2
Broos et al. (2017) reported that LA dashboards provided actionable feedback for improving learning skills.
“while Broos et al. (2017) reported that LA dashboards provided actionable feedback for improving learning skills.”
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- Premisecitation§ Educational Research Review · p. 2
The interconnection role of different dimensions of LA systems for guiding LA use in feedback activities within higher education contexts is not discussed in Cavalcanti et al. (2021).
“However, the interconnection role of different dimensions of LA systems for guiding LA use in feedback activities within higher education contexts is not discussed in this recent review study.”
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- Premisecitation§ 1.3. Learning analytics and feedback · p. 2
Several studies have offered indications that LA can support provision of meaningful and timely feedback to students.
“Several studies have offered indications that LA can support provision of meaningful and timely feedback to students (e.g. Lim et al., 2020; Zheng et al., 2021).”
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- Premisecitation§ 4.1.2. Pedagogical objectives achieved through LA-supported feedback practices · p. 10
In general, educators put a lot of time and effort to give one-by-one feedback to students in a traditional way.
“In general, educators put a lot of time and effort to give one-by-one feedback to students in a traditional way (Iraj et al., 2020).”
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- Interpretationreasoning§ 4.1.2. Pedagogical objectives achieved through LA-supported feedback practices · p. 10
Since LA-based feedback relies on each student's learning data, it makes it easier for teachers to target students who need support.
“In addition, since LA-based feedback relies on each student ' s learning data, it makes it easier for teachers to target students who need support.”
Quote in the paperNot a substantial claim - Interpretationcitation§ 4.1.2. Pedagogical objectives achieved through LA-supported feedback practices · p. 10
LA-based feedback can work as a reminder system for students to bring attention to tasks and subsequent actions.
“LA-based feedback can work as a reminder system for students to bring their attention to tasks and the subsequent actions that need to be taken (Lim et al., 2020).”
Quote in the paperNot a substantial claim - Premisecitation§ 4.1.1. LA objectives for enhancing feedback practices in higher education · p. 9
LA-based feedback assists students with modifying their learning based on their individual needs.
“LA-based feedback assists students with modifying their learning based on their individual needs (Chatti et al., 2012).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Chatti et al., 2012 source
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- Interpretationreasoning§ 4.2.1. Data used for LA feedback intervention · p. 11
Trace data plays an important role in LA-informed feedback practices because it is mostly about students' performance during learning processes.
“Trace data plays an important role in LA-informed feedback practices because this data is mostly about students ' performance during the learning processes”
Quote in the paperNot a substantial claim - Interpretationreasoning§ 4.1.2. Pedagogical objectives achieved through LA-supported feedback practices · p. 10
Based on LA insights, educators and students can modify their feedback activities.
“Based on these insights, educators, as well as students, can modify their feedback activities.”
Quote in the paperSubstantial claim - Premisecitation§ 4.1.1. LA objectives for enhancing feedback practices in higher education · p. 9
LA-based feedback can provide students with a recommendation on what to do next.
“LA-based feedback can provide students with a recommendation on what to do next (Chatti et al., 2012).”
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- Premisecitation§ 4.1.2. Pedagogical objectives achieved through LA-supported feedback practices · p. 9
The quality of students' self-regulation performance highly depends on their cognitive and metacognitive awareness of their own learning processes.
“The quality of students ' self-regulation performance highly depends on their cognitive and metacognitive awareness of their own learning processes (Karaoglan Yilmaz, 2022).”
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- Interpretationnone given§ 4.2.1. Data used for LA feedback intervention · p. 12
Without trace data, appropriate interventions by LA might not be possible.
“Reviewed publications indicate that without trace data, appropriate interventions by LA might not be possible.”
Quote in the paperNot a substantial claim - Interpretationcitation§ 4.1.2. Pedagogical objectives achieved through LA-supported feedback practices · p. 10
Students found LA-based feedback as an important factor to support their success.
“This means that students found LA-based feedback as an important factor to support their success (Pardo et al., 2019).”
Quote in the paperNot a substantial claim - Interpretationcitation§ 4.1.2. Pedagogical objectives achieved through LA-supported feedback practices · p. 10
The reason LA-based feedback can improve reflective thinking skills is that it allows students to see their progress, weaknesses, and strengths, which they can use to reflect.
“The reason why LA-based feedback can improve students ' relfective thinking skills is that feedback provided by LA allows students to see how they are doing, what are the weaknesses and strengths in their learning processes and students can use these insights to reflect on their learning processes to see what needs to be improved or modified (Yilmaz, 2020).”
Quote in the paperSubstantial claim - Interpretationreasoning§ discussed below. · p. 14
Text analytic methods were clearly helpful for exploring in-depth student perceptions, emotions, and feelings during the learning process.
“Text analytic methods were clearly helpful for exploring in-depth student perceptions, emotions, and feelings during the learning process, by digging into their qualitative data such as comments, posts, chats, etc.”
Quote in the paperNot a substantial claim - Premisecitation§ discussed below. · p. 13
Most LA reports are intended to be presented visually in a dashboard.
“In general, most LA reports are intended to be presented visually in a dashboard (e.g. Aljohani & Davis, 2013).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Aljohani & Davis, 2013
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- Interpretationreasoning§ 4.4. RQ4: how does LA support feedback stakeholders in higher education? · p. 14
LA holds great potential to provide a wide range of support not only for students but also for educators.
“These findings imply that LA holds great potential to provide a wide range of support not only for students but also for educators as well.”
Quote in the paperNot a substantial claim - Premisecitation§ discussed below. · p. 14
Text analytics is more likely used in the descriptive and diagnostic level of analytics.
“According to the level of analytics suggested by Maoz (2013; Eriksson et al., 2020), text analytics is seemed to be more likely used in the descriptive and diagnostic level of analytics.”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Maoz, 2013
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- Interpretationreasoning§ discussed below. · p. 13
Information visualization methods might be the most commonly used LA methods.
“This implies that information visualization methods might be the most commonly used LA methods.”
Quote in the paperNot a substantial claim - Premisecitation§ discussed below. · p. 13
Data mining methods alongside artificial intelligence are usually used at the predictive and prescriptive analytics levels.
“According to the level of analytics suggested by Maoz (2013; Eriksson et al., 2020), data mining methods alongside artificial intelligence are usually used at the predictive and prescriptive analytics levels.”
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- Premisecitation§ 6. A conceptual framework to guide the use of LA for feedback practices in higher education · p. 16
Objectives of the use of LA play a key role in determining what types of data are needed to collect by LA.
“objectives of the use of LA play a key role in determining what types of data are needed to collect by LA (Chatti et al., 2012).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Chatti et al., 2012 source
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- Interpretationreasoning§ 5. Discussion · p. 15
Using LA to support feedback goes far beyond simply making feedback manageable for busy, overworked educators.
“In other words, using LA to support feedback goes far beyond simply making feedback manageable for busy, overworked educators.”
Quote in the paperNot a substantial claim - Premisecitation§ 6. A conceptual framework to guide the use of LA for feedback practices in higher education · p. 16
If we do not know who are the LA stakeholders and what are the pedagogical reasons for LA application, then we cannot expect to collect the required and appropriate data.
“If we do not know who are the LA stakeholders and what are the pedagogical reasons for LA application, then, we cannot expect to collect the required and appropriate data (Banihashem & Macfadyen, 2021).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Banihashem & Macfadyen, 2021 source
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- Interpretationreasoning§ 5. Discussion · p. 15
LA can permit the provision of better, more diversified, and better-customized feedback to learners to help them acquire and develop additional learning strategies and skills.
“It can also permit the provision of better, more diversified, and better-customized feedback to learners to help them acquire and develop additional learning strategies and skills.”
Quote in the paperSubstantial claim
- Classified as probably not a substantial claim. 57
- May combine two claims. 39
- The quote only partly states this claim. 3
Probably not a substantial claim: may not pass S3 (load-bearing).
Findingreasoning§ 4.2. RQ2: what types of data does LA use to support feedback in higher education? · p. 10The data groups were divided into two main categories: data used for LA feedback intervention and data used for researching LA feedback intervention.
“we divided these groups of data into two main category including (a) data used for LA feedback intervention and (b) data used for researching LA feedback intervention”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingown data§ 3.5. Included publications · p. 5Study context varied from medicine to statistics, but studies of courses in computer science were most common (N=11, 24%).
“Study context varied - from medicine to statistics -but studies of courses in the field of computer science were found most common (N = 11, 24%).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingown data§ 3.5. Included publications · p. 5Studies from The Netherlands (N=5, 11%), Turkey (N=5, 11%), and The UK (N=3, 8%) were the next most common.
“Studies from The Netherlands (N = 5, 11%), Turkey (N = 5, 11%), and The UK (N = 3, 8%) were the next most common.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown data§ 4.1. RQ1: for what reasons is LA used in feedback studies in higher education? · p. 8Satisfaction in 1 study (2%).
“Satisfaction | 1 | 2% |”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown data§ 4.1. RQ1: for what reasons is LA used in feedback studies in higher education? · p. 8Recommendation (10 studies, 22%).
“Recommendation | 10 | 22% |”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown data§ 3.5. Included publications · p. 5Most included papers were published since 2019 (N=37, 80%).
“As shown in Table 2, most of the included papers have been published since 2019 (N = 37, 80%).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingown data§ 3.5. Included publications · p. 5Most studies were quantitative (N=28, 61%), alongside 11 qualitative studies (24%), and 7 mixed methods studies (15%).
“Most of the studies reported were quantitative (N = 28, 61%), alongside 11 qualitative studies (24%), and 7 mixed methods studies (15%).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown data§ 3.5. Included publications · p. 5A considerable number of papers reported on studies conducted in Australia of the OnTask platform (N=10, 22%).
“A considerable number of papers reported on studies conducted in Australia of the OnTask platform (N = 10, 22%).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown data§ 4.1. RQ1: for what reasons is LA used in feedback studies in higher education? · p. 8Reduce procrastination in 1 study (2%).
“Reduce procrastination | 1 | 2% |”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown data§ 4.1. RQ1: for what reasons is LA used in feedback studies in higher education? · p. 8Reflective thinking skills in 1 study (2%).
“Reflective thinking skills | 1 | 2% |”
Quote in the paperNot a substantial claimThe quote only partly states this claim.
Findingown data§ 4.1. RQ1: for what reasons is LA used in feedback studies in higher education? · p. 8Academic performance was a pedagogical objective achieved through LA-supported feedback in 17 studies (37%).
“Academic performance | 17 | 37% |”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown data§ 4.1. RQ1: for what reasons is LA used in feedback studies in higher education? · p. 8Transactional distance in 1 study (2%).
“Transactional distance | 1 | 2% |”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown data§ 3.3. Identification of relevant publications · p. 4The initial search identified 1318 papers.
“In the first phase of screening in selected databases, we identified a total of 1318 papers (Web of Science (n = 807), Scopus (n = 200), ERIC (n = 101), IEEE (n = 166), and LAK Conference contributions (n = 53)).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown data§ 3.4. Quality appraisal · p. 4All 46 studies met the minimum quality appraisal score and were included in the final analysis.
“All 46 studies in fact met the minimum score for the quality of methodology and were therefore included in the final analysis.”
Quote in the paperSubstantial claimMay combine two claims.
Findingcitation§ 4.2.2. Data used for researching LA feedback intervention · p. 12LA-based feedback underpinned by survey data can affect student cognitive load, community of inquiry, reflective thinking skills, motivation, transactional distance, and engagement.
“Reviewed publications revealed that LA-based feedback underpinned by survey data can affect student cognitive load (Sun et al., 2019; Zheng et al., 2021), the community of inquiry, reflective thinking skills (Yilmaz, 2020), motivation, and transactional distance (Yilmaz & Yilmaz, 2020), and engagement (Sun et al., 2019; Yilmaz & Yilmaz, 2021, pp. 1 -12).”
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Findingcitation§ 4.1.1. LA objectives for enhancing feedback practices in higher education · p. 9In the reviewed studies, LA was used as a recommender system to guide learners and suggest useful course material.
“In a few of the studies we reviewed, LA is used as a recommender system to guide learners and the learning process (Sedrakyan et al., 2016), and suggest useful course material (Azcona et al., 2019).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingcitation§ 4.1.2. Pedagogical objectives achieved through LA-supported feedback practices · p. 10LA-based feedback can influence students' reflective thinking skills and transactional distance.
“Furthermore, LA-based feedback can influence students ' reflective thinking skills and transactional distance (Yilmaz, 2020; Yilmaz et al., 2020).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingcitation§ 4.2.1. Data used for LA feedback intervention · p. 12Assessment data is often used by LA in feedback studies to provide recommendations, assessment, predictive feedback, and personalized feedback.
“Assessment data is often used by LA in feedback studies to provide recommendations (Lewis et al., 2021; Tempelaar et al., 2018), assessment (Chaudy & Connolly, 2019; Tempelaar et al., 2018), predictive feedback (Arnold & Pistilli, 2012; Baneres et al., 2019), and personalized feedback (Iraj et al., 2020; Lim, Gentili, et al., 2021).”
Quote in the paperNot a substantial claim0 of 3 sources checkedMay combine two claims.
Findingcitation§ 4.2.2. Data used for researching LA feedback intervention · p. 12Survey data-based LA can foster predictive feedback, recommendation, reflective feedback, and assessment.
“Selected studies suggest that survey data-based LA can foster predictive feedback (Broos et al., 2020), recommendation (Perikos et al., 2017), reflective feedback (Smith, 2020; Tsai et al., 2021), and assessment (Dalla Valle et al., 2018).”
Quote in the paperNot a substantial claim0 of 3 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing).
Findingcitation§ 4.2.1. Data used for LA feedback intervention · p. 12Demographic data is one of the most commonly employed data types in LA studies.
“This data type is one of the most commonly employed in LA studies (Azcona et al., 2019; Tempelaar et al., 2015).”
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Findingreasoning§ 4.1.2. Pedagogical objectives achieved through LA-supported feedback practices · p. 10Students with higher self-efficacy more appreciated LA-based feedback and had positive experiences with it.
“Students with higher self-efficacy more appreciated LA-based feedback and had positive experiences with it (Tsai et al., 2021).”
Quote in the paperNot a substantial claimMay combine two claims. The quote only partly states this claim.
Findingcitation§ 4.2.1. Data used for LA feedback intervention · p. 12Trace data can be used to generate reflective feedback, personalized feedback, and predictive feedback.
“Reviewed studies indicate that such data can be used to generate different types of feedback such as reflective feedback”
Quote in the paperSubstantial claimMay combine two claims.
Findingcitation§ 4.1.2. Pedagogical objectives achieved through LA-supported feedback practices · p. 10Using LA-based feedback has made it easier for educators to monitor students' learning progress and provide personalized and real-time feedback.
“However, using LA-based feedback has made it easier for educators to monitor their students ' learning progress and to provide personalized and real-time feedback (Shibani et al., 2020).”
Quote in the paperSubstantial claimMay combine two claims.
Findingreasoning§ 4.1.2. Pedagogical objectives achieved through LA-supported feedback practices · p. 10LA-based feedback can impact students' motivation and engagement.
“We found that LA-based feedback can also impact students ' motivation (e.g., Smith, 2020) and engagement (e.g., Iraj et al., 2020).”
Quote in the paperSubstantial claimMay combine two claims.
Findingcitation§ 4.1.2. Pedagogical objectives achieved through LA-supported feedback practices · p. 10If LA-based feedback relies only on warning systems, it can increase mental load, while adding encouragement can lead to higher emotional and cognitive engagement.
“If LA-based feedback relies only on warning systems, then it can increase the mental load, while putting warning systems with the encouragement of what to do can lead to higher emotional and cognitive engagement (Sun et al., 2019).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingcitation§ 4.1.2. Pedagogical objectives achieved through LA-supported feedback practices · p. 9LA-supported feedback entails real-time reflections on students' performance and personalized and reflective feedback can help students be more aware of their own learning processes to regulate their learning.
“LA-supported feedback entails real-time reflections on students ' performance during their learning processes and that personalized and reflective feedback can help students to be more aware of their own learning processes in order to regulate their learning (Lim, Gasevic, et al., 2021).”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingnone given§ 4.2.2. Data used for researching LA feedback intervention · p. 12Interview data is often supplementary data for other types of data and can offer more in-depth information.
“It is often supplementary data for other types of data that can be mined from LMS or other online platforms and can offer more in-depth information.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingcitation§ 4.2.1. Data used for LA feedback intervention · p. 12Academic history data is often combined with other types of data to provide reflective and predictive feedback, and formative assessment.
“in LA feedback studies, it is often combined with other types of data to provide reflective (Lim, Gentili, et al., 2021) and predictive feedback (Azcona et al., 2019), and formative assessment (Tempelaar et al., 2018).”
Quote in the paperNot a substantial claim0 of 3 sources checkedMay combine two claims.
Findingown data§ 4.4. RQ4: how does LA support feedback stakeholders in higher education? · p. 14In all included publications, students were mentioned as the LA-supported feedback stakeholder, followed by educators mentioned in 15 out of 46 included studies.
“As our review revealed, unsurprisingly, in all included publications, students were mentioned as the LA-supported feedback stakeholder, followed by educators mentioned in 15 out 46 included studies.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown data§ discussed below. · p. 13Information visualization methods seem to be commonly used alongside other LA methods to identify students at risk of failure and to understand student perceptions and interactions.
“Information visualization methods seem to be commonly used alongside other LA methods to identify students at risk of failure and to understand student perceptions and interactions.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingreasoning§ 4.4. RQ4: how does LA support feedback stakeholders in higher education? · p. 15At the descriptive level, LA-based feedback provides reflections on students learning activities and learning progress.
“while at the descriptive level, LA-based feedback provides reflections on students learning activities and learning progress”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingreasoning§ 4.4. RQ4: how does LA support feedback stakeholders in higher education? · p. 15At the predictive level, LA is used to predict students' retention or dropout by using data mining methods.
“at the predictive level, is to predict students ' retention or dropout by using data mining methods.”
Quote in the paperNot a substantial claimThe quote only partly states this claim.
Findingcitation§ 4.4. RQ4: how does LA support feedback stakeholders in higher education? · p. 15LA-based feedback services assist students with improving their reflective thinking skills.
“but also assist them with improving their reflective thinking skills (e.g. Yilmaz, 2020)”
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Findingcitation§ 4.4. RQ4: how does LA support feedback stakeholders in higher education? · p. 15LA-based feedback has a reminder system that helps students to be more focused and less procrastinated.
“and also has a reminder system that helps students to be more focused and less procrastinated (e.g. Lim et al., 2020).”
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Findingcitation§ discussed below. · p. 13Methods used to support feedback include predictive modelling, classification, clustering, Bayesian network analysis, natural language processing, process mining, relationship mining, support vector machine, discovery model, machine learning, and neural network.
“Methods used to support feedback include predictive modelling (Azcona et al., 2019; Tempelaar et al., 2015), classifi cation (Baneres et al., 2019), clustering (Lim, Gasevic, et al., 2021; Tempelaar et al., 2018; Tsai et al., 2021), Bayesian network analysis (Choi & Cho, 2020), natural language processing (Perikos et al., 2017), process mining (Sedrakyan et al., 2016), relationship mining (T”
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Findingcitation§ 6. A conceptual framework to guide the use of LA for feedback practices in higher education · p. 16LA feedback for students is mostly focused on their own learning performance to provide personalized feedback and to help them with regulating their learning.
“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).”
Quote in the paperSubstantial claim0 of 2 sources checkedMay combine two claims.
Findingown data§ 5. Discussion · p. 15For students, LA mostly supported students to be informed about how they are doing, reflect on their own learning process to adapt their learning based on learning needs.
“LA mostly supported students to be informed about how they are doing, reflect on their own learning process to adapt their learning based on the learning needs.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown data§ 5. Discussion · p. 15For educators, LA mainly provided insights into tracking students learning activities for timely intervention, assessing students learning progress, and early identifying students at risk.
“While for educators, LA mainly provided insights into tracking students learning activities for timely intervention, assessing students learning progress, and early identifying students ' who are at risk”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown data§ 5. Discussion · p. 15Many projects employed multiple methods.
“It is worth noting that many projects employed multiple methods.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingreasoning§ 5. Discussion · p. 15Additional data types employed are also 'about students', confirming that most LA for feedback work is student-focused and seeks to serve students as the primary stakeholders.
“Additional data types employed - demographic, assessment, and academic history data -are also 'about students ' , confirming that most LA for feedback work is student-focused and seeks to serve students as the primary stakeholders.”
Quote in the paperNot a substantial claimMay combine two claims.
Premisecitation§ 1. Introduction · p. 1High-quality feedback contributes to authentic learning by promoting student metacognitive skills and providing clear indicators of performance and areas for further improvement.
“Studies have shown that high-quality feedback contributes to authentic learning by promoting student metacognitive skills, and by providing clear indicators of performance and areas for further improvement (e.g. Callender et al., 2016; Molin et al., 2020).”
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Premisecitation§ 1. Introduction · p. 1Effective feedback is a key feature of quality teaching.
“Effective feedback represents one of the key features of quality teaching (Ramsden, 2003).”
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Premisereasoning§ 1.1. Learning analytics · p. 2Feedback as a core pedagogical practice has gained more attention in LA.
“Consequently, feedback as a core pedagogical practice has therefore gained more attention (e.g. Er et al., 2021; Misiejuk et al., 2021).”
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Premisecitation§ 1.3. Learning analytics and feedback · p. 2Van der Schaaf et al. (2017) reported that LA enhanced the quality and efficiency of feedback in professional education.
“Van der Schaaf et al. (2017) reported that LA enhanced the quality and efficiency of feedback in professional education.”
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Premisecitation§ Educational Research Review · p. 2Cavalcanti et al. (2021) provide insights into the role of automated feedback in students' performance and instructors' workload.
“For example, the recent study by Cavalcanti et al. (2021) provide insights into the role of automated feedback in students ' performance and instructors ' workload.”
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Premisecitation§ 2. Conceptualizing the review · p. 3Various analytics methods can be applied at different levels, depending on data type and LA goals.
“Various analytics methods (techniques) can be applied at different levels, depending on data type and LA goals (Chatti et al., 2012);”
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Study design and conductcitation§ 3. Method · p. 4Theelen et al.'s (2019) critical appraisal strategy was applied to review the quality of publications.
“Then, Theelen et al. ' s (2019) critical appraisal strategy was applied to review the quality of publications.”
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Premisecitation§ 2. Conceptualizing the review · p. 3LA consists of four dimensions: what (types of data), how (analytic methods), why (objectives), and who (stakeholders).
“According to this model, LA consists of four dimensions including (1) what (what types of data does the system capture and analyze), (2) how (how does the system perform analytics), (3) why (for what reasons does the system gather and analyze data), and (4) who (who is served by the analytics) (Chatti et al., 2012).”
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Study design and conductown data§ 3.6. Analytic strategy · p. 7The Kappa results showed 91 percent agreement between the two coders (κ = 0.84, p < .001), which confirms the high consistency and reliability of the coding.
“The Kappa results showed 91 percent agreement between the two coders ( κ = 0.84, p < .001), which confirms the high consistency and reliability of the coding.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ 1.1. Learning analytics · p. 2The interdisciplinary field of LA has borrowed concepts and ideas from diverse disciplines including computer science, learning science, statistics, data mining, psychology, and pedagogy.
“The interdisciplinary field of LA has borrowed concepts and ideas from diverse disciplines, including computer science, learning science, statistics, data mining, psychology, and pedagogy (Chatti et al., 2012).”
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Premisecitation§ 1.3. Learning analytics and feedback · p. 3It has been suggested that LA should be an essential component of feedback design in data-rich environments.
“and it has been suggested that LA should therefore be an essential component of feedback design in data-rich environments (Er et al., 2021; Pardo, 2018).”
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Premisecitation§ 1.3. Learning analytics and feedback · p. 2Sedrakyan et al. (2020) and Lim et al.'s (2021) found that the use of LA-based feedback supported self-regulated learning.
“Sedrakyan et al. (2020) and Lim et al. ' s (2021) found that the use of LA-based feedback supported self-regulated learning”
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Premisecitation§ 2. Conceptualizing the review · p. 3LA can serve different stakeholders - students, educators, tutors, mentors, institutions, researchers, and/or system designers.
“Finally, LA can serve different stakeholders - students, educators, tutors, mentors, institutions, re searchers, and/or system designers (Chatti et al., 2012), and no LA system can serve all stakeholders.”
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Study design and conductcitation§ 3. Method · p. 4This study adopted the PRISMA methodology for the systematic review.
“This study adopted the PRISMA methodology for the systematic review (Moher et al., 2009) to undertake a transparent process of search strategy development, definition of inclusion criteria, and identification of relevant publications.”
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Study design and conductnone given§ 3. Method · p. 4A coding scheme was developed based on the suggested theoretical framework and used to analyze the publications.
“Next, a coding scheme was developed based on the suggested theoretical framework and used to analyze these publications.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim. May combine two claims.
Study design and conductreasoning§ 3.2. Criteria for inclusion · p. 4Inclusion criteria included English language, publication from 2011 to 2022, and peer-reviewed articles in scholarly journals.
“We included only studies published in the English language (because most of the publications in this area of research are written in English). We only included publications from 2011 to 2022, since LA as a new field of study emerged in 2011. Finally, to ensure the originality, validity, and quality of selected publications, we included only peer-reviewed articles published in scholarly journals.”
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Premisecitation§ 2. Conceptualizing the review · p. 3No LA system can serve all stakeholders.
“and no LA system can serve all stakeholders.”
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Premisecitation§ 1.1. Learning analytics · p. 2LA seeks to translate learning data into knowledge that can give students insight into their own learning and enable educators to make appropriate and evidence-based interventions for the improvement of teaching and learning.
“LA seeks to translate learning data into knowledge (Wong et al., 2019) that can give students insight into their own learning, and enable educators to make appropriate and evidence-based interventions for the improvement of teaching and learning (Wise, 2014).”
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Premisecitation§ 1.3. Learning analytics and feedback · p. 3A further interesting area of work involves the use of feedback analytics to support student academic writing.
“A further interesting area of work involves the use of feedback analytics to support student academic writing (Gibson et al., 2017; Knight et al., 2020).”
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Premisecitation§ 4.2.1. Data used for LA feedback intervention · p. 12Initial LA tools were too reliant on demographic data for generating early-warning systems.
“it has been criticized that initial LA tools were too reliant on this type of data for generating early-warning systems (Ga ˇ sevi ´ c et al., 2016; Lim, Gentili, et al., 2021).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Ga ˇ sevi ´ c et al., 2016
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- cites Lim, Gentili, et al., 2021
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Interpretationreasoning§ 4.2.2. Data used for researching LA feedback intervention · p. 12Data mining methods are applied mainly on survey data.
“For this reason, data mining methods are applied mainly on survey data.”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationcitation§ 4.1.2. Pedagogical objectives achieved through LA-supported feedback practices · p. 10Insights from SNA help teachers have an overview of students' interactions and identify less engaged students to support them.
“These insights help teachers to have an overview of students ' interactions with each other and to identify which student is less engaged to support him/her.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ 4.1.2. Pedagogical objectives achieved through LA-supported feedback practices · p. 10Students with high self-efficacy are more able to execute behaviors necessary to produce a specific performance.
“This could be due to the reason that students with high self-efficacy are more able to execute behaviors that are necessary to produce a specific performance (Bandura et al., 1999).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Bandura et al., 1999 source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ discussed below. · p. 13Data mining methods mainly seek to discover patterns, correlations, and anomalies in large volumes of data.
“Generally, such methods mainly seek to discover patterns, correlations, and anomalies in large volumes of data (Lee & Siau, 2001).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Lee & Siau, 2001
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Interpretationnone given§ 4.4. RQ4: how does LA support feedback stakeholders in higher education? · p. 15LA-based recommendations and personalized feedback typically refer to LA at the prescriptive level.
“Furthermore, LA-based recommendations and personalized feedback typically refer to LA at the prescriptive level.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Interpretationcitation§ 4.4. RQ4: how does LA support feedback stakeholders in higher education? · p. 15LA services are provided at different levels of analytics according to Gartner Analytics Ascendancy Model.
“this figure illustrates that LA services are provided at different levels of analytics according to Gartner Analytics Ascendancy Model (GAAM) (Eriksson et al., 2020; Maoz, 2013).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Eriksson et al., 2020 source
Not checked in the free run.
- cites Maoz, 2013
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Premisecitation§ discussed below. · p. 13LA in predictive analytics level tells what will happen, while in prescriptive analytics level, LA recommends actions and interventions for the future.
“LA in predictive analytics level tells us ' what will happen ' , while in the prescriptive analytics level, LA recommends actions and interventions for the future (Turkington et al., 2018).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Turkington et al., 2018
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
Interpretationreasoning§ discussed below. · p. 14SNA methods are intended to be used at descriptive and diagnostic levels.
“Based on this explanation, it is expected that SNA methods are intended to be used at descriptive and diagnostic levels.”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationreasoning§ discussed below. · p. 14Network analysis methods appear to be helpful in understanding how students perceive feedback and how they reflect on their learning process alongside exploring how students interact with each other.
“Network analysis methods appear to be helpful in understanding how students perceive feedback and how they reflect on their learning process alongside exploring how students interact with each other.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Interpretationreasoning§ 4.4. RQ4: how does LA support feedback stakeholders in higher education? · p. 15Predictive feedback is expected to be provided at the predictive level.
“This implies that predictive feedback is expected to be provided at the predictive level.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable).
Interpretationreasoning§ 8. Conclusions · p. 17Effective and appropriate use of learning analytics to empower feedback practices in higher education requires the proper choice of analytics.
“the effective and appropriate use of LA to empower feedback practices in higher education requires a clear understanding of the educators ' and students ' pedagogical needs for LA support, required data to meet these needs, and the proper choice of analytics.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown data§ 7. Limitations and suggestions for future research and practice · p. 17The study did not make a distinction between educator feedback and peer feedback.
“In our findings, we did not make a distinction between educator feedback and peer feedback and how differences between these two types of feedback may lead to different use of LA in higher education contexts.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown data§ 7. Limitations and suggestions for future research and practice · p. 16The study did not investigate the effect size of different types of data to see which type can more support feedback activities.
“We also did not investigate the effect size of different types of data to see which certain type of data can more support feedback activities in higher education settings.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductcitation§ 7. Limitations and suggestions for future research and practice · p. 16There is a publication bias which means that research with null findings is often not published.
“Third, it is also important to acknowledge that there is a publication bias which means that research with null findings is often not published (Larrabee S ø nderlund et al., 2019).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Larrabee S ø nderlund et al., 2019
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Premisecitation§ 7. Limitations and suggestions for future research and practice · p. 17There is a difference between teacher feedback and peer feedback as teachers are more subject-matter experts and need less support in providing feedback.
“According to the literature, there is a difference between teacher feedback and peer feedback as teachers are more subject-matter experts with lots of feedback experiences and knowledge, and compared to students they need less support in providing feedback (Gielen et al., 2010; Paulus, 1999).”
Quote in the paperNot a substantial claim0 of 2 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ 6. A conceptual framework to guide the use of LA for feedback practices in higher education · p. 16The hierarchy of steps incorporated into the conceptual framework is in line with the findings of prior studies.
“This hierarchy of steps incorporated into our conceptual framework is in line with the findings of prior studies (e.g. Banihashem et al., 2022; Chatti et al., 2012; Elias, 2011, pp. 1 -22; Clow, 2012).”
Quote in the paperNot a substantial claim0 of 3 sources checkedClassified as probably not a substantial claim.
Premisecitation§ 6. A conceptual framework to guide the use of LA for feedback practices in higher education · p. 16Defining the recipient of the LA and the goal of the use of LA would make it clear what kind of data should be captured and analyzed.
“Defining the recipient of the LA and the goal of the use of LA would make it clear what kind of data should be captured and analyzed (Chatti et al., 2012).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Chatti et al., 2012 source
Not checked in the free run.
May combine two claims.
Interpretationreasoning§ 5. Discussion · p. 15For educators, LA was mainly used at diagnostic and predictive levels, while for students, LA was employed at descriptive and prescriptive levels.
“These findings suggest that for educators, LA was mainly used at diagnostic and predictive levels, while for students, LA was employed at descriptive and prescriptive levels.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone given§ 7. Limitations and suggestions for future research and practice · p. 17The study did not provide insights into how different categories of data are connected to different LA objectives and methods.
“However, we did not provide insights into how different categories of data are connected to different LA objectives and methods for feedback purposes in higher education.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable).
Interpretationreasoning§ 8. Conclusions · p. 17Effective and appropriate use of learning analytics to empower feedback practices in higher education requires the required data to meet educators' and students' pedagogical needs.
“the effective and appropriate use of LA to empower feedback practices in higher education requires a clear understanding of the educators ' and students ' pedagogical needs for LA support, required data to meet these needs, and the proper choice of analytics.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable).
Interpretationreasoning§ 8. Conclusions · p. 17Effective and appropriate use of learning analytics to empower feedback practices in higher education requires a clear understanding of educators' and students' pedagogical needs for learning analytics support.
“the effective and appropriate use of LA to empower feedback practices in higher education requires a clear understanding of the educators ' and students ' pedagogical needs for LA support, required data to meet these needs, and the proper choice of analytics.”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationreasoning§ 5. Discussion · p. 15LA role in the improvement of feedback practices in higher education has not been tightened to feedback itself, but also has evolved beyond the authors' first anticipation based on their proposed model.
“These findings imply that LA role in the improvement of feedback practices in higher education have not been tightened to feedback itself, but also has evolved beyond our first anticipation based on our proposed model.”
Quote in the paperSubstantial claimMay combine two claims.
Study design and conductreasoning§ 7. Limitations and suggestions for future research and practice · p. 16The review was limited to empirical studies, and some noteworthy reviews and conceptual papers may have been missed.
“First, our review was limited to empirical studies for sake of reporting only authentic findings, and we recognize that some noteworthy reviews and conceptual papers may have been missed.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone given§ 7. Limitations and suggestions for future research and practice · p. 16The selected set of literature databases may have missed studies not indexed in them.
“we acknowledge that we may have missed studies not indexed in our selected databases.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown data§ 7. Limitations and suggestions for future research and practice · p. 16The study did not provide information on identifying gaps regarding feedback features and purposes not addressed by LA in higher education.
“In this study, we did not provide information on identifying the gaps regarding the feedback features and purposes that have not been addressed by LA in higher education.”
Quote in the paperNot a substantial claimMay combine two claims.
Study design and conductreasoning§ 7. Limitations and suggestions for future research and practice · p. 16The study does not investigate LA-based feedback studies in K-12 educational contexts, so findings may not be generalizable to all modes of educational contexts.
“Fourth, while this study expands our understanding of how feedback in higher education is influenced by LA, it does not investigate LA-based feedback studies in any K-12 educational contexts. Our findings may therefore not be generalizable to all modes of educational contexts.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown data§ 7. Limitations and suggestions for future research and practice · p. 17The study's findings do not provide insights into the role of LA in features of feedback.
“In addition, our findings do not provide insights into the role of LA in features of feedback, for example how LA can influence affective, cognitive, and constructive features of feedback quality.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ 7. Limitations and suggestions for future research and practice · p. 17Providing feedback for students causes a more cognitive workload compared to teachers.
“Providing feedback for students causes a more cognitive workload compared to teachers (Noroozi et al., 2022).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Noroozi et al., 2022
Not checked in the free run.
Classified as probably not a substantial claim.
Interpretationreasoning§ 8. Conclusions · p. 17Following the steps of understanding pedagogical needs, providing required data, and choosing proper analytics leads to learning analytics being delivered properly to support feedback.
“By following these steps, we can expect to see LA is delivered properly to support feedback.”
Quote in the paperSubstantial claim
The paper relies on this without support.
Only few review studies have focused on providing an overview of the role of LA in feedback.
“However, only few review studies have focused on providing an overview of the role of LA in feedback.”
The paper relies on this without support.
According to the literature, there is no clear understanding of how LA tools can support feedback practices and how LA's use for feedback purposes in higher education can be guided.
“According to the literature, there is no clear understanding of how LA tools can support feedback practices and how LA ' s use for feedback purposes in higher education can be guided.”
The paper relies on this without support.
To date, no conceptual frameworks have been offered to guide such role of LA for the design of feedback practices.
“To date, however, no conceptual frameworks have been offered to guide such role of LA for the design of feedback practices.”
The paper relies on this without support.
There is no overview at which levels social network analysis methods can be used.
“For example, there is no overview at which levels social network analysis methods can be used.”
The paper relies on this without support.
For feedback practices in higher education, educators and students tend to be the key stakeholders.
“It might be clear that for feedback practices in higher education, educators and students tend to be the key stakeholders”
The paper relies on this without support.
Little is known about how educators and students have benefitted from LA applications in higher education.
“however, little is known about how educators and students have benefitted from LA applications in higher education?”
The paper relies on this without support.
Survey data usually contain high validity because they have already been validated by other scholars.
“What is important to note about the survey data is that this type of data usually contain a high validity, since they have already been validated by other scholars.”
The authors state this as an assumption.
The selected set of literature databases covers the most relevant publications.
“while we feel that our selected set of literature databases covers the most relevant publications”
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?
The quality of peer feedback content can be further enriched when combined with feedback from other sources, such as tutors and automated systems employing AI and learning analytics.
“Furthermore, the quality of peer feedback content can be further enriched when combined with feedback from other sources, such as tutors and automated systems employing AI and learning analytics (Banihashem et al., 2022; Farrokhnia et al., 2023; Van den Boom et al., 2007).”
From A systematic review of the key components of online peer feedback practices in higher education (2024) · cites this paper as Banihashem et al., 2022
Section 1.3 (p. 2) reports that learning analytics can support meaningful, timely feedback, so the source supports the general role of analytics in feedback. But the Limitations section (p. 17) says the review did not distinguish peer from educator feedback and provides no insight into features of feedback quality. It does not establish that combining peer feedback with tutor or automated feedback enriches the quality of peer feedback content. (LLM, conf=0.84)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
UK study percentage is too high
MinorThree of 46 studies is about 6.5%, which rounds to 7%, not 8%.
Reported 8 · recomputed 6.521739
“The UK (N = 3, 8%)”
Conference papers included despite a journals-only criterion
MinorThe inclusion criteria restrict publications to scholarly journal articles, but the final set includes six conference-proceedings papers.
“we included only peer-reviewed articles published in scholarly journals.”
“6 papers (13%) were drawn from LAK Conference Proceedings”
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A SWOT analysis of ChatGPT: Implications for educational practice and research
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“In predictive analytics, LA predicts “what will happen,” while in prescriptive analytics, it recommends future actions and interventions (Banihashem et al., 2022).”
BackgroundGenerative AI in Education: Pedagogical, Theoretical, and Methodological Perspectives
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Self-citationAssessing student perceptions and use of instructor versus <scp>AI</scp> ‐generated feedback
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Learning analytics in virtual laboratories: a systematic literature review of empirical research
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Online peer feedback in higher education: A synthesis of the literature
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Self-citationLearning analytics for online game-Based learning: a systematic literature review
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Self-citationDoes perception mean learning? Insights from an online peer feedback setting
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Self-citationExamining AI Use in Educational Contexts: A Scoping Meta-Review and Bibliometric Analysis
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A systematic review of the key components of online peer feedback practices in higher education
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Self-citationPedagogical framework for hybrid intelligent feedback
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A Current Overview of the Use of Learning Analytics Dashboards
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Vygotsky’s Creativity Options and Ideas in 21st-Century Technology-Enhanced Learning Design
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Self-citationAI vs. teacher feedback on EFL argumentative writing: a quantitative study
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Using learning analytics to explore peer learning patterns in asynchronous gamified environments
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Learning Analytics in Supporting Student Agency: A Systematic Review
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The reality of the gamification methodology in Primary Education: A systematic review
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- Authors
- Banihashem, S. K., Noroozi, O., van Ginkel, S., Macfadyen, L. P., & Biemans, H. J. A.
- Affiliations
- Open University of the Netherlands (NL)
- Wageningen University & Research (NL)
- University of British Columbia (CA)
- Corresponding author
- Banihashem, Seyyed Kazem
- Venue
- Educational Research Review
- Publisher
- Elsevier BV
- Published
- 2022-11
- Volume
- 37
- Pages
- 100489
- ISSN
- 1747-938X (ISSN-L)
- OpenAlex
- W4308066047
- Semantic Scholar
- 62b5ab72defcd780a9ee7ab258eab36d8b8fa265
- Cited by
- 246
- References
- 138
- Citations by year
- 2026: 74 · 2025: 74 · 2024: 57 · 2023: 40 · 2022: 1
- FWCI
- 7.05
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Educational Research Review (publishedVersion, cc-by)
- Socio-Environmental Systems Modeling (submittedVersion, cc-by)
- DSpace (Open University in the Netherlands) (submittedVersion, cc-by)
- Data Archiving and Networked Services (DANS) (submittedVersion, cc-by)
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Social Sciences › Education › Student Assessment and Feedback
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Keywords
- learning analytics, feedback practices, higher education, technology-mediated learning environments, conceptual framework, student feedback, analytical methods, stakeholders
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.
Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-10.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-10.
Statistics and arithmetic are recomputed, not judged.
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