Technology-mediated learning (TML) is a major trend in education, since it allows to integrate the strengths of traditional- and IT-based learning activities. However, TML providers still struggle in identifying areas for improvement in their TML offerings. One reason for their struggles is inconsistencies in the literature regarding drivers of TML performance. Prior research suggests that these inconsistencies in TML literature might stem from neglecting the importance of considering the process perspective in addition to the input and outcome perspectives. This gap needs to be addressed to better understand the different drivers of the performance of TML scenarios. Filling this gap would further support TML providers with more precise guidance on how to (re-)design their offerings toward their customers’ needs. To achieve our goal, we combine qualitative and quantitative methods to develop and evaluate a holistic model for assessing TML performance. In particular, we consolidate the body of literature, followed by a focus group workshop and a Q-sorting exercise with TML practitioners, and an empirical pre-study to develop and initially test our research model. Afterward, we collect data from 161 participants of TML vocational software trainings and evaluate our holistic model for assessing TML performance. The results provide empirical evidence for the importance of the TML process quality dimension as suggested in prior literature and highlighted by our TML practitioners. Our main theoretical as well as practical contribution is a holistic model that provides comprehensive insights into which constructs and facets shape the performance of TML in vocational software trainings.

中文翻译：

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过程为王：评估以技术为中介的学习在职业软件培训中的表现

以技术为中介的学习 (TML) 是教育的主要趋势，因为它可以整合传统和基于 IT 的学习活动的优势。然而，TML 供应商仍在努力确定他们的 TML 产品的改进领域。他们挣扎的原因之一是有关 TML 性能驱动因素的文献不一致。先前的研究表明，TML 文献中的这些不一致可能源于忽略了除了输入和结果视角之外考虑过程视角的重要性。需要解决这个差距以更好地理解 TML 场景性能的不同驱动因素。填补这一空白将进一步支持 TML 提供商，就如何（重新）设计他们的产品以满足客户的需求提供更精确的指导。为了实现我们的目标，我们结合定性和定量方法来开发和评估用于评估 TML 性能的整体模型。特别是，我们整合了大量文献，然后是焦点小组研讨会和 TML 从业者的 Q 排序练习，以及用于开发和初步测试我们的研究模型的实证预研究。之后，我们收集了 161 名 TML 职业软件培训参与者的数据，并评估了我们用于评估 TML 性能的整体模型。结果为 TML 过程质量维度的重要性提供了经验证据，正如先前文献中所建议的那样，并由我们的 TML 从业人员强调。