The impact of feedback frequency on learning and task performance: Challenging the “more is better” assumption

Lam, Chak Fu; DeRue, D. Scott; Karam, Elizabeth P.; Hollenbeck, John R.

doi:10.1016/j.obhdp.2011.05.002

Cited by 107 publications

(134 citation statements)

References 64 publications

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“…Table 1 illustrates different dimensions of feedback that can be explored. For example, immediate delivery of feedback has been shown to be effective during tasks that imposed a higher cognitive load (Kulik and Kulik 1988), but feedback at too high a frequency could be overwhelming and result in the feedback being ignored or missed (Lam et al 2011). The Surveillance Scenario could be used to explore how much feedback is too much, and the answer may depend on the team members themselves.…”

Section: Goal 2: the Surveillance Scenariomentioning

confidence: 99%

Creating a Team Tutor Using GIFT

Gilbert

Slavina

Dorneich

et al. 2017

Int J Artif Intell Educ

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With the movement in education towards collaborative learning, it is becoming more important that learners be able to work together in groups and teams. Intelligent tutoring systems (ITSs) have been used successfully to teach individuals, but so far only a few ITSs have been used for the purpose of training teams. This is due to the difficulty of creating such systems. An ITS for teams must be able to assess complex interactions between team members (team skills) as well as the way they interact with the system itself (task skills). Assessing team skills can be difficult because they contain social components such as communication and coordination that are not readily quantifiable. This article addresses these difficulties by developing a framework to guide the authoring process for team tutors. The framework is demonstrated using a case study about a particular team tutor that was developed using a military surveillance scenario for teams of two. The Generalized Intelligent Framework for Tutoring (GIFT) software provided the team tutoring infrastructure for this task. A new software architecture required to support the team tutor is described. This theoretical framework and the lessons learned from its implementation offer conceptual scaffolding for future authors of ITSs.

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Section: Goal 2: the Surveillance Scenariomentioning

confidence: 99%

Creating a Team Tutor Using GIFT

Gilbert

Slavina

Dorneich

et al. 2017

Int J Artif Intell Educ

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“…O recebimento de muitas notícias pode resultar em uma sobrecarga de informação (Lam et al, 2011) que, combinada com o efeito segunda-feira, pode resultar em rentabilidades ainda menores. Com isso, tem-se H9: em períodos de crise, os retornos na segunda-feira (em média) são menores do que o retorno das segundas-feiras fora do período de crise.…”

Section: H2unclassified

“…Assim, em períodos de incerteza/crise, a aversão a perdas pode ser ainda maior do que nos outros períodos, talvez, pela exposição a um maior volume de notícias ruins (Dzielinski, 2011) ou maior sensibilidade a elas. A sobrecarga de informações (Lam et al, 2011) em períodos de crise pode também contribuir para a obtenção de menores retornos na segunda-feira.…”

Section: Discussão Apontamentos Finais E Pesquisas Futurasunclassified

“…O recebimento de muitas notícias pode resultar em uma sobrecarga de informação (Lam, DeRue, Karam, & Hollenbeck, 2011), que estimula o viés de aversão à perda, reduzindo potencialmente as atividades de negociação dos investidores durante o período crise (Agnew & Szykman, 2005). Com isso, os resultados também foram controlados por períodos de crise/incerteza.…”

Section: Introductionunclassified

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Efeito Calendário e Finanças Comportamentais no Segmento de Fundos Multimercados

Malaquias

Mamede

2015

Rev. adm. contemp.

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O objetivo geral deste trabalho consistiu em analisar a relação entre os dias de segunda-feira com a rentabilidade proporcionada pelos fundos de investimentos multimercados brasileiros. A base final de análise foi composta por 3.337 fundos multimercados, totalizando 3.529.808 observações para dados diários, no período de janeiro/2005 a setembro/2013. Com a utilização da análise de regressão com dados em painel, levando-se em consideração variáveis de controle apontadas pela literatura como relevantes, os principais resultados indicaram que o efeito segunda-feira também ocorre no segmento de fundos de investimento, sendo intensificado por períodos de crises financeiras. Contudo constatou-se que esse efeito não foi uniforme entre todas as subcategorias de fundos multimercados. Os resultados foram persistentes entre fundos cujo prazo de resgate é D+0, bem como foram robustos ao controle pela série de retornos do Ibovespa. A discussão foi ancorada principalmente na Teoria de Finanças Comportamentais, buscando-se assim potenciais explicações para essa anomalia de mercado.

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“…Munro, Fehling, and Towne (1985) found lower error rates for learning an air intercept controller task with delayed feedback compared to immediate feedback. Delayed feedback can also lead to better decision making in organizational management tasks (Lam, DeRue, Karam, & Hollenbeck, 2011;Lurie & Swaminathan, 2009). These existing studies indicate benefits of delayed feedback for the learning of tasks that involve strategic planning and processing.…”

Section: Delayed Feedbackmentioning

confidence: 99%

Transitional feedback schedules during computer-based problem-solving practice

Johnson

Reisslein

2015

Computers & Education

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Feedback has a strong influence on effective learning from computer-based instruction. Prior research on feedback in computer-based instruction has mainly focused on static feedback schedules that employ the same feedback schedule through an instructional session. This study examined transitional feedback schedules in computer-based multimedia instruction on procedural problem-solving in electrical circuit analysis. Specifically, we compared two transitional feedback schedules: the TFS-P schedule switched from initial feedback after each problem step to feedback after a complete problem at later learning states; the TFP-S schedule transitioned from feedback after a complete problem to feedback after each problem step. As control conditions, we also considered two static feedback schedules, namely providing feedback after each practice problem-solving step (SFS) or providing feedback after attempting a complete multi-step practice problem (SFP). Results indicate that the static stepwise (SFS) and transitional stepwise to problem (TFS-P) feedback produce higher problem solving near-transfer post-test performance than static problem (SFP) and transitional problem to step (TFP-S) feedback. Also, TFS-P resulted in higher ratings of program liking and feedback helpfulness than TFP-S. Overall, the study results indicate benefits of maintaining high feedback frequency (SFS) and reducing feedback frequency (TFS-P) compared to low feedback frequency (SFP) or increasing feedback frequency (TFP-S) as novice learners acquire engineering problem solving skills.

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The impact of feedback frequency on learning and task performance: Challenging the “more is better” assumption

Cited by 107 publications

References 64 publications

Creating a Team Tutor Using GIFT

Creating a Team Tutor Using GIFT

Efeito Calendário e Finanças Comportamentais no Segmento de Fundos Multimercados

Transitional feedback schedules during computer-based problem-solving practice

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