Oliver Dickhäuser’s research while affiliated with University of Mannheim and other places

Choosing an educational path is a difficult life decision that can lead to unfavorable outcomes when it goes wrong. However, little research has examined how to support successful study major choice processes. To address this gap, we draw on person-environment fit and (affective) forecasting bias theories, assuming that higher objective major-specific fit forecasts (interests, skills, expectations) predict success (motivation, satisfaction, dropout intention, achievement) beyond subjective forecasts. Additionally relying on expectancy-value theory and cognitive dissonance theory, we assume that higher objective major-specific fit forecasts, when displayed in feedback, predict higher motivation to choose a major and higher likelihood of enrollment beyond subjective forecasts. Finally, we propose that prospective students receiving feedback before enrollment experience more success than those receiving no feedback. We tested these hypotheses in a longitudinal field study. Over three years, more than 4000 prospective students received feedback on their objective major-specific fit forecasts in an online-self-assessment and reported their motivation for the major before and after feedback. Subsequently, over 500 of these prospective students entered their respective major and reported their success. Additionally, we surveyed over 200 students who did not receive feedback. As hypothesized, objective major-specific fit forecasts predicted success beyond subjective forecasts. Higher objective forecasts related to higher motivation to choose the major and higher likelihood of enrollment beyond subjective forecasts. Finally, prospective students who received feedback on their objective forecasts before enrollment experienced more success compared to no feedback. We discuss theoretical implications for study choice and success theories and practical implications for study guidance.

Background: Achievement goals and self-efficacy are key components of teacher motivation and crucial for teaching quality and student outcomes, yet the processes explaining why they lead to specific teaching behaviors remain unclear. This study disentangles teacher goals on three levels (personal goals, student-oriented goals, intended classroom goal structures) to under-stand these processes better.Aims: We aim to uncover the associations of teachers’ personal goals and self-efficacy beliefs with specific teaching behaviors, mediated by student-oriented goals and intended classroom goal structures. Sample: 70 secondary school teachers from German general-education secondary schools, teaching Mathematics in grades 7-9 in lower track secondary education (42 women, 28 men; mean age 43.7 years, SD = 10.6) filled out a total of 345 lesson diaries over five weeks.Methods: After reporting personal goals, self-efficacy and student-oriented goals, teachers filled out standardized lesson diaries on intended classroom goal structures and specific teaching behaviors encompassing both mastery-based (interestingness, cognitive stimulation, individualization, autonomy support, structuring, collaboration, heterogeneous grouping) as well as performance-based aspects (public negative feedback, homogeneous grouping, competition). Results: Two-level path modeling indicated that personal performance goals are positively related to student-oriented performance goals, with student-oriented mastery goals being predict-ed by teachers’ self-efficacy. Intended mastery goal structures in the classroom were predicted by both student-oriented mastery goals and teachers’ personal goals and efficacy. Different linkages were observed for different teaching behaviors.Conclusions: The findings highlight the relevance of considering both student-oriented goals and intended goal structures in better understanding the relationship between teacher motivation and instructional practices.

Zusammenfassung: Bislang existierte im deutschen Sprachraum keine Skala, welche die Tendenz von Individuen erfasst, zentrale Aspekte des Selbst zu bestärken (z. B. eigene wichtige Werte). Das Ziel der vorliegenden Studie war es, eine deutsche Version des Spontaneous Self-Affirmation Measure zu validieren ( Harris et al., 2019 ): das Dispositionale Selbstaffirmationsmaß (DSAM). Hierfür führten wir eine querschnittliche Untersuchung an einer Stichprobe von Studierenden ( N = 219) und eine weitere an einer Stichprobe von Arbeitnehmenden ( N = 229) durch. Die Ergebnisse beider Studien sprechen für eine hohe Reliabilität der Skala und deuten darauf hin, dass (1) der Skala eine Bifaktor-S-1-Struktur zugrunde liegt mit einem Self-Affirmation-Generalfaktor und zwei spezifischen Inhaltsfaktoren (Affirmation durch Stärken und soziale Beziehungen). Darüber hinaus (2) sprechen die Zusammenhänge des DSAM mit anderen Selbstbestärkungsstrategien, mit Selbstintegrität und Selbstwirksamkeit für die konvergente und divergente Validität der Skala. Entgegen den Erwartungen zeigte sich jedoch kein signifikanter Zusammenhang mit Defensivität. Mit dem DSAM steht dem deutschsprachigen Raum erstmals ein validiertes Messinstrument zur Erfassung der dispositionalen Selbstaffirmation zur Verfügung.

Digital technology is considered to have great potential to promote learning in higher education. In line with the Interactive, Constructive, Active, Passive (ICAP) framework, this seems to be particularly true when instructors stimulate high-quality learning activities such as constructive and interactive learning activities instead of active and passive learning activities. Against the background of a lack of empirical studies in authentic, technology-enhanced instructional settings, we investigated the cognitive and affective-motivational effects of these learning activity modes in technology-enhanced higher education courses. To this end, we used 3.820 student assessments regarding 170 course sessions for which the teachers stated the learning activities students were engaged in. Results of multilevel structural equation modelling highlight the importance of technology-enhanced interactive learning activities for students’ perception of learning and the potential negative consequences of passive learning activities for affective-motivational outcomes. However, the superiority of constructive and interactive learning activities compared to passive and active learning activities for cognitive and affective-motivational outcomes was not supported by the findings. Instead, the findings point to potential differential effects of the individual learning activities within one activity mode. Future research should follow up on these effects to gain a more fine-grained understanding of how technology-enhanced learning activities can be optimized to enhance students’ learning outcomes.

Background Errors can provide informative feedback and exhibit a high potential for learning gains. Affective‐motivational and action‐related reactions to errors are two forms of error adaptivity that have been shown to enhance learning outcomes from errors. However, little is known regarding the development and contextual conditions of students' error reactions. A theoretically plausible facilitator to this end is the perceived error climate in the classroom. Aim We investigated how students' dealing with errors develops over time and which role the classroom context in general, and the perceived error climate in particular, has for this development. Sample A total of 1641 students participated in 69 mathematics classrooms in academic secondary schools. Methods Perceived error climate alongside students' self‐reported individual reactions to errors were assessed in a 2‐year longitudinal study with five measurement points over the fifth and sixth grade. Results Growth‐curve modelling indicated an, on average, negative development of students' individual reactions to errors. This development varied substantially between classrooms and systematically depended on perceived error climate. A more positive error climate was associated with a less negative development of error adaptivity. Conclusion Taken together, our findings imply a strong need and considerable room for the teachers' support in developing and maintaining adaptive reactions to errors. They also allow for the conclusion that teachers can succeed here by means of realizing a positive error climate in class.

Prior research has explored various factors to explain differences in teaching experiences and behaviors among school teachers, including self-efficacy, basic psychological need satisfaction, and emotions. However, these factors have predominantly been examined in isolation, and limited research has investigated their role in the context of higher education teaching. To address these research gaps, analyses on both the within and between teacher level are needed. The aim of the present study was therefore to investigate the interplay between these motivational and emotional constructs on both levels, as well as the relevance and applicability of prior research findings on school teachers to the context of higher education teaching at universities. In a micro-longitudinal study, 103 university teachers from Germany (49 female; average age: 41.4 years, SD = 11.0) completed assessments of their self-efficacy in 748 sessions directly before their teaching sessions, as well as their basic psychological need satisfaction and discrete emotions directly after. Multilevel structural equation modeling revealed positive associations between self-efficacy and basic psychological need satisfaction. Self-efficacy was negatively associated with negative emotions, and positive indirect effects on positive emotions as well as negative indirect effects on negative emotions were identified through satisfaction of the needs for competence and relatedness. Basic psychological need satisfaction was positively related to positive emotions and vice versa—however, unexpected positive associations between relatedness and negative emotions emerged and require further research.

Digital technology is considered to have great potential to promote learning in higher education, especially when instructors stimulate high-quality learning activities such as constructive and in-teractive learning activities instead of active and passive learning activities in line with the Inter-active, Constructive, Active, Passive (ICAP) framework. Against the background of a lack of empirical studies in authentic, technology-enhanced instructional settings, we investigated the cognitive and affective-motivational effects of these learning activity modes in authentic, tech-nology-enhanced higher education courses. To this end, we used 3.820 student assessments re-garding 170 course sessions for which the teachers stated the learning activities students were engaged in. Results of multilevel structural equation modelling highlight the importance of tech-nology-enhanced interactive learning activities for students’ perception of learning and the po-tential negative consequences of passive learning activities for affective-motivational out-comes. However, the superiority of constructive and interactive learning activities compared to passive and active learning activities for cognitive and affective-motivational outcomes was not supported by the findings. Instead, the findings point to potential differential effects of the indi-vidual learning activities within one activity mode. These should be followed up on in future re-search to gain a more fine-grained understanding of how technology-enhanced learning activi-ties can be optimized to enhance students’ learning outcomes.

Choosing a field of study (study major) is challenging for prospective students. However, little research has examined factors measured prior to enrollment to predict motivation and well-being in a specific study major. Based on literature on affective forecasting and person-environment fit, prospective students’ well-being forecast could be such a factor. However, affective forecasts are often biased by individuals’ inaccurate theories about what makes them happy and their misconstrual of future situations. Thus, we hypothesize that subjective and objective interest-major fit forecasts improve predictions as these factors are based on a well-founded theory (person-environment fit theory) and objective interest-major fit forecasts are additionally based on a more accurate construal of the future situation (expert estimates of a study major). We tested these hypotheses in a longitudinal field study. Over 2 years, more than 4000 prospective students were asked for their well-being forecast and subjective interest-major fit forecast before using an online-self-assessment to assess their objective interest-major fit forecast. Of these prospective students, 234 subsequently entered the psychology major and took part in a survey about their motivation and well-being in their study major. As hypothesized, higher well-being forecasts predicted higher motivation, more positive affect, and higher satisfaction in the respective major. Beyond that, higher subjective interest-major fit forecasts predicted higher motivation, less negative affect, and higher satisfaction, while objective interest-major fit forecasts incrementally predicted higher motivation, more positive affect, and higher satisfaction. We discuss theoretical implications for affective forecasting and person-environment fit theory and practical implications for study orientation and guidance.