Personalized learning (PL) is a student-centered instructional approach in which learning goals, pacing, content, and environments are customized to address individual student needs (Bernacki et al., 2021; Ellis, 2009; Lee, 2014; Miliband, 2006; Office of Educational Technology, 2010; Sota, 2016; Zhang et al., 2020). In grades K-12, PL has been described as a cornerstone of the future of education (Gross et al., 2018; Office of Educational Technology, 2010, 2016). In higher education, PL is also important for scaling and improving online learning (Alamri et al., 2020; Brown et al., 2020; Liu et al., 2017; Pelletier et al., 2022). In this chapter, we describe how "self-determination theory" ([SDT] Deci & Ryan, 1985, 2000) is well-suited for informing the design of PL in online higher education settings. Online education is a rapidly growing area of higher education (NCES, 2023) and the use of online environments for instruction produces large amounts of data in real-time that can be used to personalize learning. According to SDT, learners develop intrinsic motivation and productive self-regulatory behaviors from working in a social context in which they have autonomy, the ability to demonstrate and build competence, and a sense of belonging. In fact, Zong and Patall (this volume) discuss at length how choice provision is a beneficial design principle in PL to foster students' autonomy when choices are aligned to their personal needs and backgrounds. "Expectancy-value theory" (Wigfield & Eccles, 2000) is a related framework that explains students' achievement outcomes as a consequence of their confidence in accomplishing a task (i.e., self-efficacy) and their perceptions of the task value (i.e., the reason for pursuing the task). Lent and Brown (2002, 2019) applied concepts from these theories in their "social cognitive career theory" (SCCT), which explains contextual factors and processes in which adults develop academic and career interests, choices, and achieve goals. SCCT can guide empirical research in PL because it describes complex patterns between students' academic outcomes and choices (e.g., selecting a major, pursuing an internship) as a function of similar variables used in PL research (e.g., interests, socioeconomic background, self-efficacy). [This chapter was published in: "Handbook of Personalized Learning," Routledge, 2025, pp. 334-351.]