This thesis explores two case studies into the use of short answers and self-explanation to improve student learning in physics. The first set of experiments focuses on the role of short answer questions in the context of computer-based instruction. Through a series of six experiments, we compare and evaluate the performance of computer-assessed short answer questions versus multiple choice for training conceptual topics in physics, controlling for feedback between the two formats. In addition to finding overall similar improvements on subsequent student performance and retention, we identify unique differences in how students interact with the treatments in terms of time spent on feedback and performance on follow-up short answer assessment. In addition, we identify interactions between the level of interactivity of the training, question format, and student attitudinal ratings of each respective training. The second case study focuses on the use of worked examples in the context of multi-concept physics problems--which we call "synthesis problems." For this part of the thesis, four experiments were designed to evaluate the effectiveness of two instructional methods employing worked examples on student performance with synthesis problems; these instructional techniques, analogical comparison and self-explanation, have previously been studied primarily in the context of single-concept problems. As such, the work presented here represents a novel focus on extending these two techniques to this class of more complicated physics problem. Across the four experiments, both self-explanation and certain kinds of analogical comparison of worked examples significantly improved student performance on a target synthesis problem, with distinct improvements in recognition of the relevant concepts. More specifically, analogical comparison significantly improved student performance when the comparisons were invoked between worked synthesis examples. In contrast, similar comparisons between corresponding pairs of worked single-concept examples did not significantly improve performance. On a more complicated synthesis problem, self-explanation was significantly more effective than analogical comparison, potentially due to differences in how successfully students encoded the full structure of the worked examples. Finally, we find that the two techniques can be combined for additional benefit, with the trade-off of slightly more time-on-task. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com.bibliotheek.ehb.be/en-US/products/dissertations/individuals.shtml.]