The Impact of Cognitive and Non-Cognitive Feedback on Students' Achievement in a Distance Learning Environment

Zeichner, Orit

doi:10.26634/jet.14.4.13976

Cited by 2 publications

(7 citation statements)

References 37 publications

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“…Favourable attribution has been shown to positively affect self‐efficacy (Zeichner, 2018) and self‐efficacy to positively affect learning outcomes (Bandura, 1993; Schunk & Ertmer, 1999). Attribution in case of failure might be more or as important than attribution in case of success to influence motivational aspects and learning outcomes.…”

Section: Discussionmentioning

confidence: 99%

“…By receiving such feedback, the student should gradually shift his or her attribution for poor performance from low ability to low effort (e.g., “I made this mistake because I didn't concentrate enough.”). Previous studies have already shown an effect of attribution retraining: With more favourable attribution styles, students show increased self‐control (Banks & Woolfson, 2008), self‐efficacy (Martinez & Huber, 2019; Zeichner, 2018), and academic self‐concept (Dresel & Haugwitz, 2008; Dresel & Ziegler, 2006). Hence, they should invest more effort, perform better, and ultimately have higher learning outcomes (Horner & Gaither, 2004; Houston, 2016).…”

Section: Introductionmentioning

confidence: 96%

“…Self‐efficacy can be influenced by attributional feedback as Martinez and Huber (2019) showed in their review. In this present study, we focus on self‐efficacy in a mathematical context as in “I feel confident that I can solve this task without help.” In a distant learning environment, Zeichner (2018) found in a sample of 171 high school students higher reported self‐efficacy scores in students who received attributional feedback in comparison to students who only received cognitive feedback. Therefore, it is not enough to simply give cognitive feedback on the student's answer, especially in settings of self‐regulated learning.…”

Section: Introductionmentioning

confidence: 99%

“…Thus, newer studies used automated, computer‐based re‐attributional feedback instead of verbal or written teacher feedback to increase density and showed promising results (Dresel & Haugwitz, 2008; Hamm et al, 2017; Lazowski & Hulleman, 2016; Zeichner, 2018). The computer‐based approach allows not only giving re‐attributional feedback to every student at the same time.…”

Section: Introductionmentioning

confidence: 99%

“…With more favourable attribution styles, students show increased self-control (Banks & Woolfson, 2008), self-efficacy (Martinez & Huber, 2019;Zeichner, 2018), and academic self-concept (Dresel & Haugwitz, 2008;Dresel & Ziegler, 2006). Hence, they should invest more effort, perform better, and ultimately have higher learning outcomes (Horner & Gaither, 2004;Houston, 2016).…”

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confidence: 99%

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Digital re‐attributional feedback in high school mathematics education and its effect on motivation and achievement

Whalen,

Renkl,

Eitel

et al. 2023

Computer Assisted Learning

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BackgroundStudents often show unfavourable attribution: they attribute poor school performance to stable factors such as lack of ability and good school performance to variable factors such as effort. However, attribution can be influenced by individualized digital re‐attributional feedback leading to positive motivational effects and higher learning outcomes. This is very promising, but it still is unclear, whether this digital re‐attributional feedback can also be successfully integrated in everyday classroom activities.ObjectivesThe present field experiment investigated how integrating digital re‐attributional feedback into classroom instruction affects student attribution, motivation and learning outcomes.MethodsIn the experiment, 8th–10th grade high school students (N = 322) worked with a digital mathematics learning program which was integrated in a three‐week teaching unit. Half the students in each classroom received only standard feedback after each practice task (SF group); the other half received additionally an individual re‐attributional feedback (RF group) after every third task. Attribution, mathematics self‐concept, and self‐efficacy were measured by an online questionnaire twice a week; learning outcomes in mathematics were measured weekly.Results and ConclusionHierarchical analyses showed that re‐attributional feedback led to a more favourable attribution in case of success on stable factors. Especially low‐performing students benefited from this feedback. No effects on attribution in case of failure, self‐efficacy or learning outcomes could be found. Further research could investigate if certain adaptations to the digital re‐attributional feedback is more effective in a real classroom setting and has a broader impact on different students.

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Section: Discussionmentioning

confidence: 99%