Atieh Emily L, York Darrin M, Muñiz Marc N
Department of Chemistry and Chemical Biology and Cyberlearning Innovation and Research Center, Rutgers, The State University of New Jersey, Piscataway, New Jersey 08854-8087, United States.
J Chem Educ. 2021 Feb 9;98(2):281-292. doi: 10.1021/acs.jchemed.0c01074. Epub 2020 Dec 29.
As the conversation in higher education shifts from diversity to inclusion, the attrition rates of students in the STEM fields continues to be a point of discussion. Combined with the demand for expansion in the STEM workforce, various retention reforms have been proposed, implemented, and in some cases integrated into policy following evidence of success. Still, new findings, technological advances, and socio-cultural shifts inevitably necessitate an on-going investigation as to how students approach learning. Among other factors, students who enter college without effective study skills are at much greater risk of being unsuccessful in their coursework. In order to construct an equitable learning environment, a mechanism must be developed to provide underprepared students with access to resources or interventions designed to refine the skills they need to be successful in the course. Early, reliable assessments can provide predictions of individual student outcomes in order to guide the development and implementation of such targeted interventions. In the present study, a model is developed to predict students' odds of success based their study approaches, as measured by their responses to twelve survey items from an existing instrument used in the Chemistry Education Research literature designed to measure students' deep and surface learning approaches. The model's prediction specificity ranges from 66.5% to 86.9% by semester. Two distinct sets of lower-performing students are identified in the data: those who align predominantly with surface approaches to learning versus those who indicate using both deep and surface approaches to learning. This supports the idea of a tailored approach to interventions, rather than a one-size-fits-all solution. Results from this instrument were correlated to students' reported study methods and beliefs.
随着高等教育领域的讨论重点从多样性转向包容性,理工科领域学生的流失率仍是一个讨论焦点。鉴于对理工科劳动力扩张的需求,在有成功证据之后,已提出、实施了各种留用改革措施,有些情况下还将其纳入了政策。然而,新的研究发现、技术进步和社会文化变革不可避免地需要持续调查学生的学习方式。在诸多因素中,那些进入大学时没有有效学习技能的学生在课程学习中面临更大的失败风险。为了构建一个公平的学习环境,必须建立一种机制,为准备不足的学生提供获取资源或干预措施的途径,以提升他们在课程中取得成功所需的技能。早期、可靠的评估可以预测个别学生的学习成果,从而指导此类针对性干预措施的制定和实施。在本研究中,开发了一个模型,根据学生的学习方式来预测他们成功的几率,学生的学习方式通过他们对化学教育研究文献中一种现有工具的十二个调查项目的回答来衡量,该工具旨在测量学生的深层和表层学习方式。该模型按学期计算的预测特异性范围为66.5%至86.9%。数据中识别出两组不同的表现较差的学生:一组主要采用表层学习方式,另一组则表示同时采用深层和表层学习方式。这支持了采取量身定制的干预方法,而不是一刀切的解决方案这一观点。该工具的结果与学生报告的学习方法和信念相关。