In this chapter, we provide an overview of the design, data-collection, and data-analysis efforts for a digital learning and assessment environment for scientific inquiry / science practices called "Inq-ITS" ("I"nquiry "I"ntelligent "T"utoring "S"ystem; www.inqits.org). We first present a brief literature review on current science standards, learning sciences research on students' difficulties with scientific inquiry practices, and modern assessment design frameworks. We then describe how we used pilot data from four case studies with hands- on inquiry tasks for middle school students to better understand these difficulties and design various components of the Inq-ITS system to support students' inquiry accordingly. Lastly, we describe how we used key computational techniques from knowledge-engineering and educational data mining to analyze data from students' log files in this environment to (1) automatically score students' inquiry skills, (2) provide teachers with fine-grained, rich, classroom-based formative assessment data on these practices, and (3) react in real time to scaffold students as they engage in inquiry. [This paper was published in: Rupp, A.A. & Leighton, J.P (Eds.) "The Wiley Handbook of Cognition and Assessment: Frameworks, Methodologies, and Applications." West Sussex, UK (pp. 508-534).]