This paper presents the dataset collected from student interactions with INQPRO, a computer-based scientific inquiry learning environment. The dataset contains records of 100 students and is divided into two portions. The first portion comprises (1) "raw log data", capturing the student's name, interfaces visited, the interface components the student interacted with, the actions performed by the students and the values asserted at a particular interface component; (2) "transformed log data", a restructured and refined raw log data that take the form of an attribute-value pair record. The second portion of the dataset consists of pretest-posttest results. This paper begins with an overview of INQPRO and the discussion on how student-computer interactions were captured. Subsequently, the process of preprocessing and transformation of raw log data into relational database tables will be presented. In this paper, two applications of INQPRO dataset are presented; the first application discusses how students' levels of scientific inquiry skills can be extracted from the dataset while the second application demonstrates how the dataset supports the prediction of conceptual change occurrence. The paper ends with highlighting potential future research work by using this dataset, which includes techniques to elicit clusters of students as well as provision of adaptive pedagogical interventions as the student interacts with INQPRO. In conclusion, this dataset attempts to contribute to the research community through: (1) time and cost saving in acquiring field data, and (2) as a benchmark dataset to evaluate and compare different predictive models.