With the expansion of the online learning scale and the rapid development of learning analysis techniques, learning systems can completely record learners’ online learning behavior. What types of learning intervention measures can influence learning performance? How is the intervention working? The above questions are the focus of online courses and emphasize improving the online learning effect. In this research, 96 undergraduates (Classes 1 and 2, Grade 2) majoring in civil engineering and enrolled in the Engineering Surveying online course at the College of Transportation Engineering, Huanghe Jiaotong University, Henan Province, were selected as the research objects and randomly divided into two groups (the experimental group (N = 48) and the control group (N = 48)). Then, conducted a 15-week sustained intervention study through quasi-experimental research, and verified the effectiveness of different types of intervention measures on the learners’ learning performance. Next, a one-way analysis of variance was conducted, based on the pretesting of the performance data, the quality of online discussion posts, the effective learning duration, and the online final test results. Research results showed no obvious differences between the experimental group and control group in the online final test results from the previous semester (P = 0.347). The online learners’ learning performance was influenced by three aspects of the learning intervention, that is, apparent differences in the posting quality in the learning prompt intervention (T = 8.23, P < 0.01), the online learning duration in the process monitoring intervention (T = 23.19, P < 0.01), and the online final test results in the achievement incentive intervention (T = 6.08, P < 0.01). The research results have an important reference value for implementing intervention strategies in the online learning environment, judging the effectiveness of such strategies according to curve changes in performance, and using the mass data of learners recorded by online learning platforms.