Learning in settings with partial feedback and the wavy recency effect of rare events

Plonsky, Ori; Erev, Ido

doi:10.1016/j.cogpsych.2017.01.002

Cited by 38 publications

(37 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…(Nevo & Erev, ) In decisions from experience, agents are commonly engaged in choice inertia (repeating the most recently chosen option (Ashby & Teodorescu, ; Biele et al, ): Model‐based analysis of behavior in this paradigm estimated the likelihood of inertia at over 70% of the choices. (Plonsky & Erev, ) According to “surprise triggers change,” rare (thus, surprising) events increase the likelihood that choice inertia discontinues. Therefore, rare events tend to increase the likelihood for a switch in choice (beyond the pure effect of the reinforcement).…”

Section: Why Is the Effect Of Forgone‐worse Information Different In mentioning

confidence: 99%

“…Specifically, consider participants who choose the status quo option in Problem 4RD and get feedback concerning outcomes worse than their obtained outcomes (i.e., Conditions All‐Forgone and Only‐Worse‐Forgone) such that if a −10 is happened to be drawn in the risky option, they would observe it as a forgone loss. According to surprise triggers change, this surprising event would then increase the likelihood they would switch their choice to the risky option in the next trial (i.e., a negative recency effect (Plonsky et al, ; Plonsky & Erev, )). That is, unlike in other problems, in rare disaster environments, exposure to worse forgone outcomes would tend to increase the risky rates.…”

Section: Why Is the Effect Of Forgone‐worse Information Different In mentioning

confidence: 99%

See 1 more Smart Citation

The influence of biased exposure to forgone outcomes

Plonsky

Teodorescu

2020

Behavioral Decision Making

Self Cite

View full text Add to dashboard Cite

After making decisions, we often get feedback concerning forgone outcomes (what would have happened had we chosen differently). Yet, many times, our exposure to such feedback is systematically biased. For example, your friends are more likely to tell you about a party you missed if it was fun than if it was boring. Despite its prevalence, the effects of biased exposure to forgone outcomes on future choice have not been directly studied. In three studies (five experiments) using a simplified learning task, we study the basic influence of biased exposure to forgone outcomes in the extreme case in which decision makers can easily infer the missing information such that the biased exposure carries almost no informational value. The results in all studies suggest that nevertheless, the biased exposure to forgone outcomes affected choice. Exposure to forgone outcomes only when they were better than the obtained outcomes (Only‐Better‐Forgone) increased selections of the forgone option compared with exposure to forgone outcomes only when they were worse than the obtained outcome (Only‐Worse‐Forgone). Moreover, relative to an unbiased exposure to all forgone outcomes, the effect of exposure to Only‐Worse‐Forgone was larger than the effect of exposure to Only‐Better‐Forgone feedback. However, these effects were not universal: In environments that include rare negative events (“disasters”), biased exposure to forgone outcomes had very little effect. We raise potential explanations and further discuss implications for marketing and risk awareness.

show abstract

Section: Why Is the Effect Of Forgone‐worse Information Different In mentioning

confidence: 99%

Section: Why Is the Effect Of Forgone‐worse Information Different In mentioning

confidence: 99%

The influence of biased exposure to forgone outcomes

Plonsky

Teodorescu

2020

Behavioral Decision Making

Self Cite

View full text Add to dashboard Cite

show abstract

“…The majority of narratives occurred during participants' postsecondary studies. In part, the sharing of these particular narratives may reflect participants' increased knowledge and abilities to recognize mental health challenges, chronological proximity to the onset of mental health challenges, relational proximity to relevant details and events, and recency effects (i.e., high memory for recent events; Plonsky & Erev, 2017).…”

Section: Content Analysismentioning

confidence: 99%

Sharing Narratives to Foster Mental Health Literacy in Teacher Candidates

Woloshyn

Savage

2018

cjsotl-rcacea

View full text Add to dashboard Cite

This study explored the nature of teacher candidates’ mental health narratives in the context of completing an elective course in mental health and wellness. How students deconstructed their narratives and the narratives of their peers over time was also explored. Participants included 67 fourth-year students completing a five-year concurrent teacher education program. Data was collected over two academic years and consisted of students’ beginning-of-course and end-of-course narratives. The narratives were analyzed using content and thematic analysis. The findings are discussed in the context of using shared narratives as case study to promote self-reflection, discussion, problem-solving and mental health literacy within undergraduate courses. Cette étude explore la nature des récits sur la santé mentale racontés par des étudiants à l’enseignement en train de terminer un cours sur la santé mentale et le bien-être. Nous avons exploré la manière dont les étudiants ont décortiqué leurs récits ainsi que les récits de leurs pairs au fil du temps. Les participants consistaient de 67 étudiants de quatrième année inscrits dans un programme concomitant de formation des enseignants de cinq ans. Nous avons recueilli des données au cours de deux années universitaires; ces données représentaient des récits d’étudiants racontés au début du cours et à la fin du cours. Les récits ont été étudiés grâce à une analyse du contenu et des thèmes. Les résultats sont discutés dans le contexte du partage des récits en tant qu’études de cas afin de promouvoir l’auto-réflexion, la discussion, la résolution de problèmes et la compréhension de la santé mentale dans les cours de premier cycle.

show abstract

“…The outcome of 32 may be so tempting that the participant stops sampling and chooses Option A for the final decision. Likewise, in the negative domain (e.g., Problem 2: A −3 B 0 A −3 B 0 A −3 B 0 A −3 B −32 ), a participant might stop sampling after a large negative outcome, akin to the “hot‐stove” effect (Denrell, ; Plonsky & Erev, ).…”

Section: The Relation Between Optional Stopping and Final Decisionsmentioning

confidence: 99%

“…, a participant might stop sampling after a large negative outcome, akin to the "hot-stove" effect (Denrell, 2007;Plonsky & Erev, 2017).…”

Section: The Relation Between Optional Stopping and Final Decisionsmentioning

confidence: 99%

Switch rates do not influence weighting of rare events in decisions from experience, but optional stopping does

Soo

Rottman

2018

Behavioral Decision Making

View full text Add to dashboard Cite

The current research investigates how people decide which of two options produces a better reward by repeatedly sampling from the options. In particular, it investigates the roles of two features of search, optional stopping and switch rate, on participants' final judgments of which option is better. First, in two studies, we found evidence for a new optional stopping effect; when participants stopped sampling right after experiencing a rare outcome, they made decisions as if they overweighted the rare outcome. Second, we investigated an effect proposed by Hills and Hertwig (2010) that people who frequently switch between options when sampling are more likely to make decisions consistent with underweighting rare outcomes. We conducted a theoretical analysis examining how switch rate can influence underweighting and how the type of decision problem moderates this effect. Informed by the theoretical analysis, we conducted four studies designed to test this effect with high power. None of the studies produced significant effects of switch rate. Lastly, the studies replicated a prior finding that optional stopping and switch rate are negatively correlated. In sum, this research elaborates a fuller understanding of the relation between search strategies (switch rate and optional stopping) on how people decide which option is better and their tendency to overweight versus underweight rare outcomes.

show abstract

Learning in settings with partial feedback and the wavy recency effect of rare events

Cited by 38 publications

References 53 publications

The influence of biased exposure to forgone outcomes

The influence of biased exposure to forgone outcomes

Sharing Narratives to Foster Mental Health Literacy in Teacher Candidates

Switch rates do not influence weighting of rare events in decisions from experience, but optional stopping does

Contact Info

Product

Resources

About