Excessive use of digital technology has been linked to undesirable outcomes, including low social connectedness and poor academic performance. Effective use of digital learning tools can no doubt enhance adolescents’ learning. However, they should be aware that excessive use of digital technology has a significant potential to waste valuable time that could be spent studying and may lead to social isolation, as they often connect to their smart devices instead of spending time with friends in person. They may grow up to be more isolated. The Academic Distraction theme is shaped by the participant’s experience of digital technology overuse, interrupting their studies. The participants noted and acknowledged that they were distracted from studies by excessive internet use, social media, online gaming, and smartphones. They revealed that they cannot control their behaviour in the presence of negative implications for their academic achievement. Recurrent descriptors included being out of control, losing control, and unable to regain control. This paper implements the proposed digital distraction detection algorithm (DDA) to detect social media distractions for students’ tests. It is then compared against the other three algorithms, Digi Track Predictor (DTP), Tech Impact Predictor (TIP), and Digital Distraction Prevention Algorithm (DDPA). The performance of the proposed DDA algorithm exceeds other algorithms proposed in the literature.