This systematic review examines the implementation and impact of formative assessment methods in introductory programming courses in higher education. Formative assessments, which provide ongoing feedback, play a crucial role in improving teaching effectiveness and student learning. This review explores a range of strategies, such as ungraded practice quizzes, peer assessments, gamified activities, and AI-enhanced feedback tools, and evaluates their effectiveness across four key domains: student engagement, motivation, learning outcomes, and programming skills. These constructs were selected to reflect both affective and cognitive-behavioral outcomes essential for success in programming education. The review is based on 25 empirical studies published between 2020 and 2024, selected through a systematic search of the Scopus and Web of Science databases and screened using PRISMA guidelines. Findings show that well-designed formative assessments foster interactive, personalized, and low-pressure learning environments, especially benefiting novice programmers. The most effective methods align with learner needs and provide immediate feedback, promoting both conceptual understanding and practical skills. The review concludes that diverse, adaptive, and context-sensitive formative assessment strategies can significantly enhance student success and should guide the design of future programming courses and educational technologies.