This study evaluates the quality and effectiveness of contextually personalized programming exercises generated by GPT-4 in an introductory programming course. The exercises were created to align with students' interests and cultural backgrounds, aiming to enhance engagement and learning outcomes. The study involved both the authors and students in evaluating the exercises, with students providing feedback on their usefulness and engagement. The results showed that the exercises generated by GPT-4 were generally of high quality, and students found them engaging and useful. The study also examined how students interacted with the tool, finding that they preferred choosing themes over random exercises, suggesting that context personalization could effectively increase student engagement. The study highlights the potential of generative AI in computing education, offering a practical and unlimited pool of personalized exercises for students. The findings suggest that AI-generated programming problems can be a valuable addition to introductory programming courses, as they provide students with tailored practice material that aligns with their personal interests and educational needs. The study also addresses the challenges of creating contextually personalized exercises, including ensuring the exercises are relevant, clear, and appropriately challenging for students. The results indicate that context personalization can positively impact student engagement and learning outcomes, making it a promising approach in computing education.This study evaluates the quality and effectiveness of contextually personalized programming exercises generated by GPT-4 in an introductory programming course. The exercises were created to align with students' interests and cultural backgrounds, aiming to enhance engagement and learning outcomes. The study involved both the authors and students in evaluating the exercises, with students providing feedback on their usefulness and engagement. The results showed that the exercises generated by GPT-4 were generally of high quality, and students found them engaging and useful. The study also examined how students interacted with the tool, finding that they preferred choosing themes over random exercises, suggesting that context personalization could effectively increase student engagement. The study highlights the potential of generative AI in computing education, offering a practical and unlimited pool of personalized exercises for students. The findings suggest that AI-generated programming problems can be a valuable addition to introductory programming courses, as they provide students with tailored practice material that aligns with their personal interests and educational needs. The study also addresses the challenges of creating contextually personalized exercises, including ensuring the exercises are relevant, clear, and appropriately challenging for students. The results indicate that context personalization can positively impact student engagement and learning outcomes, making it a promising approach in computing education.