Impact of Personalized Feedback: The Case of Coaching and Learning Change Plans

Lockyer, Jocelyn; Armson, Heather; Könings, Karen D.; Zetkulic, Marygrace; Sargeant, Joan

doi:10.1007/978-3-030-25112-3_11

Cited by 4 publications

(3 citation statements)

References 39 publications

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“…Table 2 outlines recommendations for both educator and program development to apply analytics to CCC processes. Rich LA can enhance trainee development and foster a growth mindset promoting self-reflection, self-directed learning, and co-production of ILPs [ 1 , 7 , 17 , 25 , 28 , 48–51 ].…”

Section: Educator Development and Learning Analyticsmentioning

confidence: 99%

“…Learning analytics is the interpretation of multiple data sources gathered on trainees to assess academic progress, predict future performance, and identify potential issues to be addressed with feedback and individualized learning plans (ILPs) [ 15 , 17 , 18 ]. What distinguishes LA from other educational approaches is systematic data collection and advanced digital interpretation and visualization to inform educational systems [ 19 , 20 ].…”

Section: Introductionmentioning

confidence: 99%

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Using learning analytics in clinical competency committees: Increasing the impact of competency-based medical education

Carney

Sebok‐Syer

Pusic

et al. 2023

Medical Education Online

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Graduate medical education (GME) and Clinical Competency Committees (CCC) have been evolving to monitor trainee progression using competency-based medical education principles and outcomes, though evidence suggests CCCs fall short of this goal. Challenges include that evaluation data are often incomplete, insufficient, poorly aligned with performance, conflicting or of unknown quality, and CCCs struggle to organize, analyze, visualize, and integrate data elements across sources, collection methods, contexts, and time-periods, which makes advancement decisions difficult. Learning analytics have significant potential to improve competence committee decision making, yet their use is not yet commonplace. Learning analytics (LA) is the interpretation of multiple data sources gathered on trainees to assess academic progress, predict future performance, and identify potential issues to be addressed with feedback and individualized learning plans. What distinguishes LA from other educational approaches is systematic data collection and advanced digital interpretation and visualization to inform educational systems. These data are necessary to: 1) fully understand educational contexts and guide improvements; 2) advance proficiency among stakeholders to make ethical and accurate summative decisions; and 3) clearly communicate methods, findings, and actionable recommendations for a range of educational stakeholders. The ACGME released the third edition CCC Guidebook for Programs in 2020 and the 2021 Milestones 2.0 supplement of the Journal of Graduate Medical Education (JGME Supplement) presented important papers that describe evaluation and implementation features of effective CCCs. Principles of LA underpin national GME outcomes data and training across specialties; however, little guidance currently exists on how GME programs can use LA to improve the CCC process. Here we outline recommendations for implementing learning analytics for supporting decision making on trainee progress in two areas: 1) Data Quality and Decision Making, and 2) Educator Development.

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Section: Educator Development and Learning Analyticsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Using learning analytics in clinical competency committees: Increasing the impact of competency-based medical education

Carney

Sebok‐Syer

Pusic

et al. 2023

Medical Education Online

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“…R2C2 is a reflective model developed and extensively field-tested in Canada, the Netherlands and the USA to guide productive feedback interchanges led by postgraduate supervisors in a range of clinical specialisms (Sargeant et al 2018;Lockyer et al 2019). It aims to be a facilitative, learner-centred approach, stimulating reflection and underpinning self-assessment.…”

Section: Example Fourmentioning

confidence: 99%

Feedback in Postgraduate Online Learning: Perspectives and Practices

Hounsell

2021

Postdigital Science and Education

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Reimagining the Clinical Competency Committee to Enhance Education and Prepare for Competency-Based Time-Variable Advancement

et al. 2022

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Assessing residents and clinical fellows is a high-stakes activity. Effective assessment is important throughout training so that identified areas of strength and weakness can guide educational planning to optimize outcomes. Assessment has historically been underemphasized although medical education oversight organizations have strengthened requirements in recent years. Growing acceptance of competency-based medical education and its logical extension to competency-based time-variable (CB-TV) graduate medical education (GME) further highlights the importance of implementing effective evidence-based approaches to assessment. The Clinical Competency Committee (CCC) has emerged as a key programmatic structure in graduate medical education. In the context of launching a multi-specialty pilot of CB-TV GME in our health system, we have examined several program’s CCC processes and reviewed the relevant literature to propose enhancements to CCCs. We recommend that all CCCs fulfill three core goals, regularly applied to every GME trainee: (1) discern and describe the resident’s developmental status to individualize education, (2) determine readiness for unsupervised practice, and (3) foster self-assessment ability. We integrate the literature and observations from GME program CCCs in our institutions to evaluate how current CCC processes support or undermine these goals. Obstacles and key enablers are identified. Finally, we recommend ways to achieve the stated goals, including the following: (1) assess and promote the development of competency in all trainees, not just outliers, through a shared model of assessment and competency-based advancement; (2) strengthen CCC assessment processes to determine trainee readiness for independent practice; and (3) promote trainee reflection and informed self-assessment. The importance of coaching for competency, robust workplace-based assessments, feedback, and co-production of individualized learning plans are emphasized. Individual programs and their CCCs must strengthen assessment tools and frameworks to realize the potential of competency-oriented education.

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Impact of Personalized Feedback: The Case of Coaching and Learning Change Plans

Cited by 4 publications

References 39 publications

Using learning analytics in clinical competency committees: Increasing the impact of competency-based medical education

Using learning analytics in clinical competency committees: Increasing the impact of competency-based medical education

Feedback in Postgraduate Online Learning: Perspectives and Practices

Reimagining the Clinical Competency Committee to Enhance Education and Prepare for Competency-Based Time-Variable Advancement

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