GAME-BASED TRAINING: AN EFFECTIVE METHOD FOR REDUCING BEHAVIORAL-FINANCE BIASES

F. Tommasi, Andrea Ceschi, Marija Gostimir, Marco Perini, R. Sartori
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Abstract

Nowadays, being able to understand and infer reasonable conclusions based on great amounts of numerical information represents a key competence to succeed both in education and work. Numeracy is defined as the ability to understand, think, and reason using numbers and math concepts. Such a competence is key in the field of behavioral-finance where individuals manage numerical information to face important choices. Indeed, numeracy is fundamental to analyze data and to make predictions on the likelihood of future events. Moreover, research shows that individuals who score high on numeracy report higher ability in creating alternative options when it turns to make decisions. Building on the computer-supported collaborative learning and on the technology acceptance model, this study aimed to evaluate the efficacy of different interventions to reduce psychological biases related to numerical information processes in a group of university students (N = 800). Specifically, we devised two training interventions based on the two educational approaches, i.e., the computer-supported collaborative learning and on the technology acceptance model. Participants were randomly assigned to one of the two conditions, and -post measures were collected after the interventions to assess their numerical information processing ability. Moreover, post-training results were compared with the results of a control group. Results of a one-way ANOVA showed that in the control group reported the highest incidence of numeracy biases. Our preliminary findings support the main literature on the use of technological instruments and distant training as keys to develop cognitive and operational competences. Such results are limited since we were unable to collect -pre-measures of participants’ numeracy biases. Overall, the present contribution provides initial insights into how different kind of technology-based trainings can be effective to reduce biases referred to numerical information processing.
基于游戏的训练:减少行为金融学偏差的有效方法
如今,能够根据大量的数字信息理解并推断出合理的结论是在教育和工作中取得成功的关键能力。计算能力被定义为使用数字和数学概念理解、思考和推理的能力。这种能力是行为金融学领域的关键,在这个领域中,个人管理数字信息来面对重要的选择。事实上,计算能力是分析数据和预测未来事件可能性的基础。此外,研究表明,计算能力得分高的人在做决定时创造替代选项的能力更高。基于计算机支持的协作学习和技术接受模型,本研究旨在评估不同干预措施对减少与数字信息处理相关的心理偏差的效果。具体而言,我们基于计算机支持的协作学习和技术接受模型这两种教育方法设计了两种培训干预措施。参与者被随机分配到两种条件之一,并在干预后收集-post测量来评估他们的数字信息处理能力。此外,将训练后的结果与对照组的结果进行比较。单因素方差分析的结果显示,在对照组中报告的计算偏差发生率最高。我们的初步研究结果支持了主要文献关于使用技术工具和远程培训是发展认知和操作能力的关键的观点。这样的结果是有限的,因为我们无法收集参与者的计算偏差的预先测量。总的来说,目前的贡献提供了关于不同类型的基于技术的培训如何有效减少涉及数字信息处理的偏见的初步见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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