The Role of Explanations in Casual Observational Learning about Nutrition

Abstract

The ubiquity of internet-based nutrition information sharing indicates an opportunity to use social computing platforms to promote nutrition literacy and healthy nutritional choices. We conducted a series of experiments with unpaid volunteers using an online Nutrition Knowledge Test. The test asked participants to examine pairs of photographed meals and identify meals higher in a specific macronutrient (e.g., carbohydrate). After each answer, participants received no feedback on the accuracy of their answers, viewed proportions of peers choosing each response, received correctness feedback from an expert dietitian with or without expert-generated explanations, or received correctness feedback with crowd-generated explanations. The results showed that neither viewing peer responses nor correctness feedback alone improved learning. However, correctness feedback with explanations (i.e., modeling) led to significant learning gains, with no significant difference between explanations generated by experts or peers. This suggests the importance of explanations in social computing-based casual learning about nutrition and the potential for scaling this approach via crowdsourcing.

The use of social media in nutrition interventions for adolescents and young adults—A systematic review

“…In other such studies, researchers are using social media posts to learn about food choice influences [75], to incorporate photosharing of meals [81,82], and to allow users to collectively reflect on the food environment [83]. Though not targeted towards young people, others have explored social collaborative learning for collectively identifying healthy diet through food image tagging [84,85] and improving nutritional knowledge through crowdsourcing [86,87]. Another area that has received considerable attention outside the clinical domain is gamification.…”

Crowdsourcing Treatments for Low Back Pain

“…Related work suggests that with adequate support the output of non-professionals can be improved to match that of the professionals in many cases [5,21,28]. In our study, the best treatments by non-professionals were assessed very similarly to the best by professionals.…”

“…For example, in learning about nutrition, expert-generated-explanations, i.e. short descriptions that experts used to justify the correct answers, were found as highly useful in training non-experts [5]. In addition to experts' feedback, comparing one's own contributions to the comparative frequencies of others' contributions has been shown to rapidly improve workers' expertise in voting-based tasks [21].…”

Intervenções fundamentadas no letramento alimentar: Revisão de escopo conforme a renda do país

“…Assim, 10 artigos adotam o termo LA (Gilliland et al, 2015;Wallace et al, 2016;Krummel et al, 2017;Slatter, 2017;Urbina et al, 2017;Begley et al, 2019;Garcia et al, 2019;Palermo et al, 2019;George & Gerde, 2020;Tuuri et al, 2020). O termo LN ou em nutrição está em sete publicações (Silk et al, 2008;Duncan et al, 2012;Burgermaster et al, 2017;Parekh et al, 2017;Rochman et al, 2018;Abdi et al, 2019;Marchello et al, 2020). Duas publicações utilizaram os dois termos, LA e LN ou em nutrição (Porter et al, 2016;Mitsis et al, 2019).…”

“…Embora não explicitadas em todos os estudos, as ações desenvolvidas atendem aos domínios do LA, ou seja, planejamento e gestão; seleção, preparação e culinária; e alimentação (Begley et al 2019). Houve seis estudos que tiveram grupo controle (Duncan et al, 2012;Burgermaster et al, 2017;Parekh et al, 2017;Mitsis et al, 2019;Marchello et al, 2020;Tuuri et al, 2020), sendo 4 americanos, um grego e um australiano. Os demais estudos avaliaram resultados apenas através do diagnóstico da situação pré e pós-intervenção imediata.…”