The purpose of this research was to investigate the effects of formative assessment and learning style on student achievement in a Web-based learning environment. A quasi-experimental research design was used. Participants were 455 seventh grade students from 12 classes of six junior high schools. A Web-based course, named BioCAL, combining three different formative assessment strategies was developed. The formative assessment strategies included Formative Assessment Module of the Web-Based Assessment and Test Analysis system (FAM-WATA) (with six Web-based formative assessment strategies), Normal Module of Web-Based Assessment and Test Analysis system (N-WATA) (only with partial Web-based formative assessment strategy) and Paper and Pencil Test (PPT) (without Web-based formative assessment strategy). Subjects were tested using Kolb's Learning Style Inventory, and assigned randomly by class into three groups. Each group took Web-based courses using one of the formative assessment strategies. Pre-and post-achievement testing was carried out. A one-way ANCOVA analysis showed that both learning style and formative assessment strategy are significant factors affecting student achievement in a Webbased learning environment. However, there is no interaction between these two factors. A post hoc comparison showed that performances of the FAM-WATA group are higher than the N-WATA and PPT groups. Learners with a 'Diverger' learning style performed best followed by, 'Assimilator', 'Accommodator', and 'Converger', respectively. Finally, FAM-WATA group students are satisfied with six strategies of the FAM-WATA.

In this paper, three mathematical models are established to explore the factors that influence the price of used sailboat, and predicts the price of used sailboat in different regions. First, clean and process the dataset, and the node centrality analysis is carried out. Next, a decision tree model is used to explain the price of the sailboat. In order to predict the price of sailing ships in different regions, this paper transforms geographical region variables into dummy variables, and uses multiple linear regression method to evaluate the influence of geographical region on the price. Then, an ANOVA model is established to analyze the price and regional impact of different types of sailboats. Finally, a cluster analysis algorithm is established to classify used sailboat by various classification factors.