Bick Nathalie, Froehlich Laura, Voltmer Jan-Bennet, Raimann Jennifer, Reich-Stiebert Natalia, Seidel Niels, Burchart Marc, Martiny Sarah E, Nikitin Jana, Stürmer Stefan, Martin Andreas
CATALPA - Center of Advanced Technology for Assisted Learning and Predictive Analytics, FernUniversität in Hagen, Hagen, Germany.
Department of Psychology, FernUniversität in Hagen, Hagen, Germany.
Front Psychol. 2024 Sep 13;15:1346503. doi: 10.3389/fpsyg.2024.1346503. eCollection 2024.
Collaboration improves multiple academic and social outcomes. Accordingly, computer-supported collaborative learning (CSCL) can be beneficial in distance education contexts to overcome the issues specific to online learning (e.g., underperformance, low identification with university). Distance universities often attract a substantial number of non-traditional students (e.g., students with disability, students with migration background). Despite their representation, non-traditional students face negative stereotypes and associated social consequences, including social identity threat, diminished sense of belonging, and less motivation for social interactions. In the context of online learning, where there is little individuating information, social categories like socio-demographic group memberships become salient, activating stereotypes. Consequently, socio-demographic group memberships can have detrimental consequences for the integration of non-traditional students. The purpose of the present study was to (a) determine the extent of social identity threat for students in higher distance education, (b) explore the social consequences of this threat in the same context, (c) validate these findings through longitudinal analyses embedded in a CSCL task, and (d) use learning analytics to test behavioral outcomes. In a longitudinal study with three measurement occasions over 8 weeks ( = 1,210), we conducted path analyses for cross-sectional associations and Random Intercept Cross-Lagged Panel Models for longitudinal predictions. The results showed that non-traditional students mostly reported higher social identity threat than traditional students. While the expected longitudinal within-person effects could not be demonstrated, we found stable between-person effects: students who reported higher levels of social identity threat also reported lower sense of belonging and lower social approach motivation. Exploratory analyses of actual online collaboration during CSCL offer potential avenues for future research. We conclude that social identity threat and its social consequences play an important role in higher distance education and should therefore be considered for successful CSCL.
合作能改善多种学术和社会成果。因此,计算机支持的协作学习(CSCL)在远程教育环境中可能有益,有助于克服在线学习特有的问题(如表现不佳、对大学的认同感低)。远程大学通常吸引大量非传统学生(如有残疾的学生、有移民背景的学生)。尽管有这些学生群体的存在,但非传统学生面临负面刻板印象及相关的社会后果,包括社会身份威胁、归属感降低以及社交互动的动力不足。在在线学习环境中,由于个体信息较少,社会人口统计学群体成员等社会类别变得突出,从而激活了刻板印象。因此,社会人口统计学群体成员身份可能对非传统学生的融入产生不利影响。本研究的目的是:(a)确定高等远程教育中学生的社会身份威胁程度;(b)探索这种威胁在同一背景下的社会后果;(c)通过嵌入CSCL任务的纵向分析验证这些发现;(d)使用学习分析来测试行为结果。在一项为期8周、有三次测量时机的纵向研究中(n = 1210),我们对横断面关联进行了路径分析,并对纵向预测采用了随机截距交叉滞后面板模型。结果表明,非传统学生大多报告比传统学生有更高的社会身份威胁。虽然未能证明预期的个体内部纵向效应,但我们发现了稳定的个体间效应:报告社会身份威胁水平较高的学生也报告了较低的归属感和较低的社交接近动机。对CSCL期间实际在线协作的探索性分析为未来研究提供了潜在途径。我们得出结论,社会身份威胁及其社会后果在高等远程教育中起着重要作用,因此在成功开展CSCL时应予以考虑。