Validation Reconceived
The Double Treatment Experimental Design
Bibliographic Data
| ID | 22167569 |
|---|---|
| Authors | Tobias Halbherr (ETH Zurich, corresponding author), Manu Kapur (0000-0002-2232-6111, ETH Zurich) |
| Year | 2020 |
| Volume | 4 |
| Publication date | 2020-01-22 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Education (JOURNAL) |
| Journal identifiers | ISSN: 2504-284X • E-ISSN: 2504-284X |
| Publisher | Frontiers Media SA (PUBLISHER • CH) |
| DOI | 10.3389/feduc.2019.00156 |
| OpenAlex | W3001192844 |
| Language | EN |
| Citations received | 1 |
| References cited | 3 |
Learning is a process that leads to outcomes. The science of learning is the epistemic practice of investigating the relationship between this process and its outcomes. We propose a novel method for the study of learning: The Double Treatment experimental design. The core design for experimental studies in the Learning Sciences consists of two elements, learning activities together with assessments of their outcomes. In conventional Single Treatment experimental designs, the learning activities are subject to a controlled experimental manipulation, the outcomes of which are then evaluated in a common assessment. In the Double Treatment experimental design, both the learning activity and the assessment are subject to the experimental manipulation, leading to a basic 2 x 2 experimental design. We provide a theoretical rationale in favor of the Double Treatment design, which we illustrate and discuss in three experimental study examples implementing this method: A study on the contextual nature of memorization and recall while scuba diving, a study on invention activities as a preparation for future learning, and a study on resource-rich assessment in computer science. We argue that the Double Treatment design has the potential to enhance the epistemic power of experimental Learning Sciences research by improving the ontological coherence of experimental designs. They promise to facilitate both hypothesis testing and hypothesis generation, enable the validation of assessment methods from within corresponding studies, and reduce the need for externally validated assessments outside the control of the researchers
Design of experiments · Experiential learning · Learning Sciences · Management science · Mathematics education · Memorization · Research design · Computer Science · Engineering · Innovative Teaching and Learning Methods · Mathematics · Online Learning and Analytics · Psychology · Software Engineering Research · Artificial Intelligence
| Unique citing works | 1 |
|---|---|
| Citations per year | 1 |
| Citation span | 2026 - 2026 (1) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 1 |