Data Mining Intern

Program: Mathematics, Science, & Technology Program
Time Commitment: 20-50% time for 3-4 months

WestEd, a nonprofit research, development, and service agency, works with education and other communities to promote excellence, achieve equity, and improve learning for children, youth, and adults. While WestEd serves the states of Arizona, California, Nevada, and Utah as one of the nation's Regional Educational Laboratories, our agency's work extends throughout the United States and abroad. WestEd has 17 offices nationwide, from Washington and Boston to Arizona, Southern California, and its headquarters in San Francisco.

WestEd's Mathematics, Science, & Technology (MST) Program is committed to increasing mathematics, science and technology literacy among our nation's youth. The program offers services, materials, and strategies that support teachers' professional growth in content knowledge, effective teaching practices, appropriate assessment and evaluation.

MST covers issues from culture and language to earth science and international science education. In addition, MST staff increase communication, public awareness, and understanding about mathematics, science and technology education and advance research in this area.

International studies show that U.S. students rank near the bottom in science and mathematics. The MST program seeks to reverse this trend by helping prepare teachers to meet the learning needs of all students.

Position Description

The ChemCollective Virtual Lab is a flexible, multimedia learning environment designed to help students connect procedural knowledge of mathematical formalisms with authentic chemistry learning by allowing them to design and carry out experiments. In the Embedded Assessments in the ChemCollective Virtual Lab project, WestEd and Carnegie Mellon University will extend the utility of this existing software by developing activities with interactive embedded assessments for two of the most difficult and central topics in introductory chemistry: Stoichiometry and Chemical Thermodynamics.

The goals of this project are to: 1) Create Virtual Lab activities with embedded assessments that are aligned with core high school chemistry content and inquiry standards, 2) Create individualized coaching that is responsive to student behaviors and allows each student to progress at his or her own pace, and 3) Develop a reporting system that enables students to monitor their own progress and allows teachers to quickly see overall patterns in student performance, so that they may tailor their ongoing instruction.

The Virtual Lab activities will allow students to develop and demonstrate deeper levels of understanding of both chemistry content and inquiry skills. The activities will be designed as embedded assessments, and students will receive coaching to allow them to work according to individual skill levels. Reports will allow students to monitor their progress and provide teachers with information they need to monitor instructional progress in the course. We expect these activities to lead to improvements in science achievement as students develop a deeper understanding of chemical principles and increased ability to plan and conduct laboratory investigations.

For the initial phase of this project, we seek an intern to analyze detailed log files, at the mouse click level, of college students using the Virtual Lab to solve problems in stoichiometry and thermodynamics. The intern will use data mining and log file analysis to identify patterns of actions in the Virtual Lab that are linked with successful and unsuccessful problem solving. We will use the data to determine what series of interactions with the laboratory equipment and chemicals typically lead to success and which patterns are associated with difficulties. The identified patterns will allow us to develop coaching that helps struggling students but does not interfere with students that are making progress on their own. The intern will:

1. Carryout data mining of log files to identify patterns of student behavior associated with successful and unsuccessful problem-solving performance.
2. Identify key problem-solving steps that may be diagnostic of successful performance.
3. Develop representations to communicate findings of data mining.
4. Assist in writing reports that present the methodology and findings of the log file analysis.

Qualifications

• Master's degree in science, computer science, educational technology or related field (Doctoral student preferred).
• Experience with log file analysis and data mining.
• Experience with machine learning and computational modeling.
• Strong organizational, communication and presentation skills.
• Knowledge of introductory college-level chemistry.
• Interest in applying computational skills to educational issues.

Apply online