In computer science education, introductory computer programming courses tend to be the most challenging for novices, with higher dropout rates than other computer science courses. Recruitment and retention of students in computer science fields is an important area of focus in computer science education research, and previous research has considered many classroom approaches. Collaborative practices in the classroom in particular have contributed to lower dropout rates, with structured practices such as pair programming resulting in higher quality code products and increasing retention of students in computer science majors. While pair programming has shown many benefits, there are still challenges to consider. Incompatible partners and getting stuck during collaboration both contribute negatively to the learning experience. Instructors can help mitigate some situations, but this solution is not scalable to large classrooms. Adaptive support systems specifically designed to support collaboration show great promise, achieving similar outcomes to human tutors. The collaborative process must be investigated more deeply in order to determine how exactly such systems can best support students. The goal of this dissertation work was to advance the state of knowledge around how undergraduate students collaborate on computer science tasks through pair programming. In my work, I have modeled and compared the problem-solving approaches of individual students and students pairs, examined the differences between the dialogue of more successful and less successful pairs, and revealed the ways in which learners expressed and addressed uncertainty. My work has identified three recommendations for how to best support students during pair programming in the context of addressing and resolving uncertainty: students should (1) notify partner when uncertainty is resolved; (2) focus on resolving current uncertainty before proceeding with the task; and (3) explain their current thought process to their partner. Through a Wizard-of-Oz design, I implemented an adaptive support protocol in the form of textual prompts displayed during collaboration, with the goal of comparing the coding product and collaborative process outcomes of student pairs that received adaptive support and student pairs that did not. I hypothesized that student pairs receiving adaptive support would create higher quality programs, express higher confidence in their solution, exchange more dialogue utterances with each other, and evaluate their partners more favorably than student pairs that did not receive adaptive support. I found no significant differences in these outcomes. Upon closer examination of how students received the adaptive support prompts, I found that most of the prompts did not appear to influence students' behaviors. The events that did cause a reaction from the students helped inform the following design recommendations for adaptive technology designers: manage user expectations, understand users' expertise, consider the language of any prompts, and provide validation feedback. These findings advance our understanding of moments of uncertainty during pair programming and provide design insights for designers of adaptive technologies to support collaboration in computer science education. [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.]