abstract: This study empirically evaluated the effectiveness of the instructional design, learning tools, and role of the teacher in three versions of a semester-long, high-school remedial Algebra I course to determine what impact self-regulated learning skills and learning pattern training have on students' self-regulation, math achievement, and motivation. The 1st version was a business-as-usual traditional classroom teaching mathematics with direct instruction. The 2rd version of the course provided students with self-paced, individualized Algebra instruction with a web-based, intelligent tutor. The 3rd version of the course coupled self-paced, individualized instruction on the web-based, intelligent Algebra tutor coupled with a series of e-learning modules on self-regulated learning knowledge and skills that were distributed throughout the semester. A quasi-experimental, mixed methods evaluation design was used by assigning pre-registered, high-school remedial Algebra I class periods made up of an approximately equal number of students to one of the three study conditions or course versions: (a) the control course design, (b) web-based, intelligent tutor only course design, and (c) web-based, intelligent tutor + SRL e-learning modules course design. While no statistically significant differences on SRL skills, math achievement or motivation were found between the three conditions, effect-size estimates provide suggestive evidence that using the SRL e-learning modules based on ARCS motivation model (Keller, 2010) and Let Me Learn learning pattern instruction (Dawkins, Kottkamp, & Johnston, 2010) may help students regulate their learning and improve their study skills while using a web-based, intelligent Algebra tutor as evidenced by positive impacts on math achievement, motivation, and self-regulated learning skills. The study also explored predictive analyses using multiple regression and found that predictive models based on independent variables aligned to student demographics, learning mastery skills, and ARCS motivational factors are helpful in defining how to further refine course design and design learning evaluations that measure achievement, motivation, and self-regulated learning in web-based learning environments, including intelligent tutoring systems. / Dissertation/Thesis / Ph.D. Educational Technology 2013

Hands-on experiential learning activities are an important component of computing education disciplines. Laboratory environments provide learner access to real world equipment for completing experiments. Local campus facilities are commonly used to host laboratory classes. While campus facilities afford hands-on experience with real equipment high maintenance costs, restricted access, and limited flexibility diminish laboratory effectiveness. Web-based simulation and remote laboratory formats have emerged as low cost options, which allow open access and learner control. Simulation lacks fidelity and remote laboratories are considered too complex for novice learners. A web-based combined laboratory format incorporates the benefits of each format while mitigating the shortcomings. Relatively few studies have examined the cognitive benefits of web-based laboratory formats in meeting computing education students’ goals. A web-based combined laboratory model that incorporates motivation strategies was developed to address non-traditional computing education students’ preferences for control of pace and access to learning. Internal validation of the laboratory model was conducted using pilot studies and Delphi expert review techniques. A panel of instructors from diverse computing education backgrounds reviewed the laboratory model. Panel recommendations guided enhancement of the model design.