Student – Feedback Interaction Model: Revised

Lipnevich, Anastasiya A.; Smith, Jeffrey K.

doi:10.1016/j.stueduc.2022.101208

Cited by 31 publications

(20 citation statements)

References 63 publications

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“…The idea of student receptivity is based on the premise that there may be individual differences in how people are willing or ready (or not) to accept feedback (Lipnevich & Smith, 2009;Lipnevich et al, 2016;Murano et al, 2021). Some students may generally be eager to receive external comments on their progress or performance, whereas others may be less welcoming.…”

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confidence: 99%

“…It is now uniformly accepted by researchers and practitioners alike that feedback is only effective if it is used, and it will only be used if a student has the right context, information, dispositions, and approach to how to use it. Lipnevich et al (2016) described a model of student/feedback interaction, where they discussed feedback information, the student as the recipient of feedback, and how the two interact. One of the key learner characteristics that the authors discussed was student receptivity to instructional feedback (RIF).…”

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confidence: 99%

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Receptivity to Instructional Feedback

Lipnevich

Lopera-Oquendo

2024

European Journal of Psychological Assessment

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Abstract. The purpose of this study was to report validity evidence for the instrument intended to measure receptivity to instructional feedback in a sample of secondary school students from Singapore ( N = 314). We tested a nested hierarchy of hypotheses for addressing the cross-group (i.e., gender) invariance and compared means on the receptivity to feedback subscales between gender groups. We also examined whether receptivity to feedback predicted student grades. The four-factor hypothesized model comprising experiential attitudes, instrumental attitudes, cognitive engagement, and behavioral engagement with feedback had a good model fit. Multi-group confirmatory factor analysis supported configural, metric, partial scalar, partial strict as well as variance and covariance invariance across gender groups. After controlling for gender, cognitive engagement, and experiential attitudes predicted increments in grades, suggesting evidence for discriminant validity among the receptivity factors as well as their relevance for the prediction of meaningful educational outcomes.

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Receptivity to Instructional Feedback

Lipnevich

Lopera-Oquendo

2024

European Journal of Psychological Assessment

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“… Feedback can play a pivotal role in learning, but it is only effective when students engage with it (Hattie & Timperley, 2007; Kluger & DeNisi, 1996; Wisniewski et al, 2020). Individual levels of feedback receptivity have been shown to relate to differences in recipients’ response to and use of feedback in educational psychology (Hedgcock & Lefkowitz, 1994; Lipnevich & Smith, 2022; Panadero & Lipnevich, 2021), industrial and organizational psychology (Linderbaum & Levy, 2010; London & Smither, 2002), and medical psychology (Mills et al, 2023). Therefore, current feedback discussions and models emphasize the central role that receptivity to feedback in the feedback process plays in explaining the differences in feedback effectiveness (Lipnevich & Panadero, 2021).…”

Section: Receptivity To Instructional Feedback (Rif)mentioning

confidence: 99%

Receptivity to Instructional Computer-Based Feedback (RIF)

Luca Bahr,

Höft,

Meyer

et al. 2024

European Journal of Psychological Assessment

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Feedback can play a pivotal role in learning but is only effective when students use it. However, the use of feedback varies greatly from student to student and these differences must be explained. Hence, the construct receptivity to instructional feedback (RIF) was introduced to assess students’ attitudes towards and engagement with human-provided feedback in multiple English-speaking countries. However, RIF scales have not yet been used in computer-based assessment contexts nor in German-speaking countries; their application is thus limited. This study examined an adapted and translated RIF scale using confirmatory factor analysis (CFA) and exploratory structural equation modeling (ESEM). We capitalized on data sets comprising German-speaking university ( N = 464) and secondary school ( N = 1,207) students. The bifactor-CFA model showed a good model fit and revealed a general receptivity factor alongside the four specific factors: experiential attitudes, instrumental attitudes, cognitive engagement, and behavioral engagement with feedback. Scalar measurement invariance allowed for cross-gender and educational level comparisons. The relationships with broader personality characteristics were consistent with other contexts, thus indicating discriminant validity. General receptivity, cognitive engagement, and experiential attitudes positively correlated with GPA, suggesting convergent validity. Results support the stability of the RIF scale’s adaptation and translation. Assessment implications are discussed.

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“…Feedback, far from only being information provided to the learner from the instructor, is a process that actively and purposefully involves the learner (Carless, 2015) with engagement and agency on feedback received (Handley et al, 2011;Lipnevich et al, 2016;Nieminen et al, 2022;Winstone et al, 2017). Formative assessment and feedback are crucial drivers of student learning and are strictly interconnected (Hattie & Clarke, 2018;Hattie & Timperley, 2007;Lipnevich et al, 2016;Lui & Andrade, 2022;Shute, 2008;Smith & Lipnevich, 2018). However, formative assessment and feedback relationships do not denote a linear input-output response (Esterhazy, 2019).…”

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confidence: 99%

“…Within this framework, a principled course, assessment, and feedback design sustain several opportunities for encounters with feedup, feed-back and feed-forward feedback types at three levels (task, process, and self-regulatory) (Brooks et al, 2019;Hattie & Timperley, 2007). Students engage with feedback that comes from different agents (Evans, 2013;Hattie & Timperley, 2007;Lipnevich et al, 2016) before, during, and after assessment Esterhazy, 2019).…”

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Learner perceptions of the feedback process in the online component of a blended course

Moni

2024

OLJ

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Despite extensive research on feedback models, there is still sparse empirical evidence of their validity and application in higher education learning settings, whether online, hybrid, or face-to-face. Understanding how a feedback framework, integrated in the instructional cycle, is perceived by the learners can provide empirical support about its intended purpose and effectiveness. Recent reviews of research on student perceptions of feedback in different learning environments have revealed the need to research feedback as a process with the use of a more solid methodological approach. The aim of the present descriptive survey study is to investigate learners’ perceptions of an established feedback model, a Matrix of Feedback for Learning (Brooks et al., 2019), in the asynchronous online component of an undergraduate blended course. More specifically, the impact of its application on learners’ encounters with three types of feedback (feed-up, feed-back and feed-forward) and three levels of feedback (task, process and self-regulatory) is explored. A 36-item survey, previously piloted and preliminarily validated, was used to explore learners’ perceptions (N=135) of the three feedback types and levels. Approximately 68% of responses showed that students recognized feedback and the possibilities to use and act on feedback as helpful to their learning. This present survey supports a line of research on feedback model validation in online learning environments while offering meaningful insights from the learners that can inform both course design and interventions to support engagement with feedback.

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Student – Feedback Interaction Model: Revised

Cited by 31 publications

References 63 publications

Receptivity to Instructional Feedback

Receptivity to Instructional Feedback

Receptivity to Instructional Computer-Based Feedback (RIF)

Learner perceptions of the feedback process in the online component of a blended course

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