Videos have long been viewed through the free choice of customers, but in some cases currently, watching them is absolutely required, for example, in institutions, companies, and education, even if the viewers prefer otherwise. In such cases, the video provider wants to determine whether the viewer has honestly been watching, but the current video viewing judging system has many loopholes; thus, it is hard to distinguish between honest viewers and false viewers. Time interval different answer popup quiz (TIDAPQ) was developed to judge honest watching. In this study, TIDAPQ randomly inserts specially developed popup quizzes in the video. Viewers must solve time interval pass (RESULT 1) and individually different correct answers (RESULT 2) while they watch. Then, using these two factors, TIDAPQ immediately performs a comprehensive judgement on whether the viewer honestly watched the video. To measure the performance of TIDAPQ, 100 experimental subjects were recruited to participate in the model verification experiment. The judgement performance on normal watching was 93.31%, and the judgement performance on unusual watching was 85.71%. We hope this study will be useful in many areas where watching judgements are needed.

This study explores the effects of worked-out examples and metacognitive scaffolding on novice learners’ knowledge performance, cognitive loads, and self-regulation skills in problem-solving programming. 126 undergraduate students in a computer programming fundamentals course were randomly assigned to one of four groups: 1) task performance with a traditional WOE (TW), 2) task performance with a faded WOE (FW), 3) task performance with traditional WOE and metacognitive scaffolding (TWM), and 4) task performance with a faded WOE and metacognitive scaffolding (FWM). Over the course of 3 weeks, participants in these four groups were asked to solve programming problems using Python with WOE and metacognitive scaffolding. The results demonstrate that the provision of metacognitive scaffolding with faded WOE (FWM) is the most effective for problem-solving programming and self-regulation skills. In addition, an interaction effect exists between the two treatments for the germane load in FWM. Therefore, results in this study provide empirical insights into ways to effectively apply WOE and metacognitive scaffolding to problem-solving processes for programming-based complex problem-solving, especially for novice learners.