Comparing Pedagogical Approaches for the Acquisition and Long-Term Robustness of the Control of Variables Strategy By: Michael São Pedro Advisor: Janice.

Slides:



Advertisements
Similar presentations
October 12, A Look at Pedagogical Content Knowledge Overview Curriculum: Biology Content Pre-Assessment using CPS Reflection Instruction: What do.
Advertisements

Inquiry-Based Instruction
Is it Mathematics? Linking to Content Standards. Some questions to ask when looking at student performance Is it academic? – Content referenced: reading,
Increasing your confidence that you really found what you think you found. Reliability and Validity.
California Educational Research Association Annual Meeting San Diego, CA November 18 – 19, 2010 Terry Vendlinski Greg Chung Girlie Delacruz Rebecca Buschang.
Experimental Design: Threats to Validity. EXPERIMENTS: The independent variable is manipulated to determine its effect on the dependent variable(s) whilst.
Tradeoffs Between Immediate and Future Learning: Feedback in a Fraction Addition Tutor Eliane Stampfer EARLI SIG 6&7 September 13,
Assessment Policies 1 Implementation and Monitoring American Institutes for Research February 2005.
Specialized Understanding of Mathematics: A Study of Prospective Elementary Teachers Meg Moss.
A retrospective look : Action Research on the Fly:
Planning for Inquiry The Learning Cycle. What do I want the students to know and understand? Take a few minutes to observe the system to be studied. What.
Does Schema-Based Instruction and Self-Monitoring Influence Seventh Grade Students’ Proportional Thinking? Asha Jitendra, University of Minnesota Jon R.
Technological Pedagogical Content Knowledge How do you.
MATH IN THE MIDDLE MICHAEL A. COBELENS. Problem Solving Identify Learning Experiences Purpose: Methods of Teaching Problem Solving and Computational Skills.
Network Routing Algorithms Patricia Désiré Marconi Academy, CPS IIT Research Mentor: Dr. Tricha Anjali This material is based upon work supported by the.
Inquiry.
Contrasting Examples in Mathematics Lessons Support Flexible and Transferable Knowledge Bethany Rittle-Johnson Vanderbilt University Jon Star Michigan.
Inquiry. Inquiry is a term that we often hear when we are talking about science teaching. How do you define “inquiry”?
Collaborating for Student Success Using Collaborative Inquiry with Student Teachers to Support Teacher Professional Development Sponsored by Teachers for.
Science Inquiry Minds-on Hands-on.
Chapter 6 Using Indirect Teaching Methods. The Discussion Method w Classroom goals: Questions that explore controversial issues (with no simple answer)
 Inquiry-Based Learning Instructional Strategies Link to Video.
DEVELOPING ALGEBRA-READY STUDENTS FOR MIDDLE SCHOOL: EXPLORING THE IMPACT OF EARLY ALGEBRA PRINCIPAL INVESTIGATORS:Maria L. Blanton, University of Massachusetts.
Scientific Inquiry: Learning Science by Doing Science
Katie McEldoon, Kelley Durkin & Bethany Rittle-Johnson 1.
Group Discussion Explain the difference between assignment bias and selection bias. Which one is a threat to internal validity and which is a threat to.
1 How can self-regulated learning be supported in mathematical E-learning environments? Presenters: Wei-Chih Hsu Professor : Ming-Puu Chen Date : 11/10/2008.
Developing teachers’ mathematics knowledge for teaching Challenges in the implementation and sustainability of a new MSP Dr. Tara Stevens Department of.
Measuring Changes in Teachers’ Mathematics Content Knowledge Dr. Amy Germuth Compass Consulting Group, LLC.
Measuring Changes in Teachers’ Science Content Knowledge Dr. Anne D’Agostino Compass Consulting Group, LLC.
Quasi-Experimental Designs For Evaluating MSP Projects: Processes & Some Results Dr. George N. Bratton Project Evaluator in Arkansas.
Dissertation Theme “The incidence of using WebQuests on the teaching-learning process of English Foreign Language (EFL) for students attending the seventh.
Jacqueline Wroughton. 1. There are n set trials, known in advance 2. Each trial has two possible outcomes (success/failure). 3. Trials are independent.
Prompts to Self-Explain Why examples are (in-)correct Focus on Procedures 58% of explanations were procedure- based Self-explanation is thought to facilitate.
Online Video Usefulness: The Effect of Self- Explanation on Learning Christopher J. Devers, Erin E. Devers, Allie Alayan, and Cody Reaves Indiana Wesleyan.
Aptitude by Treatment Interactions and Gagné’s Nine Events of Instruction Dr. K. A. Korb University of Jos.
1 Multimedia-Supported Metaphors for Meaning Making in Mathematics Moreno & Mayer (1999)
“I think it's much more interesting to live not knowing than to have answers which might be wrong.” -Richard P. Feynman.
Construct-Centered Design (CCD) What is CCD? Adaptation of aspects of learning-goals-driven design (Krajcik, McNeill, & Reiser, 2007) and evidence- centered.
EXPERIMENTAL DESIGN Science answers questions with experiments.
Rachel Wing DiMatteo 1 Daniel Heck 2 Mark Driscoll 1 Johannah Nikula 1 Research-based Professional Development Materials Increase Geometric Thinking 1.
Second Language Classroom Research (Nunan, D. 1990) Assoc. Prof. Dr. Sehnaz Sahinkarakas.
Imagine science classrooms in which: The teacher pushes a steel needle through a balloon and the balloon does not burst. The teacher asks the students.
Capturing Growth in Teacher Mathematical Knowledge The Association of Mathematics Teacher Educators Eleventh Annual Conference 26 January 2007 Dr. DeAnn.
IRIS CENTER Learning Outcomes for IRIS Online Modules Used in College Courses Project # H325F OSEP Project Directors’ Conference Washington, DC July.
National Research Conference on Strengthening School- Based Management
Leena Razzaq and Neil T. Heffernan Venu Babu Thati Hints: Is It Better to Give or Wait to Be Asked? 1.
Improving Intrinsic Motivation in Reading: Effects of Reading Strategies Instruction Group members 陳毓茜 (Nancy) 鐘晨嫚 (Edith) 宋盛郁 (Ellen)
Understanding the Science MSP Mark Watrin Science Coordinator ESD112 Questioning and Investigating Investigate an answerable question through valid experimental.
Standards-Based Science Assessment. Ohio’s Science Cognitive Demands Science is more than a body of knowledge. It must not be misperceived as lists of.
The Impact of Student Self-e ffi cacy on Scientific Inquiry Skills: An Exploratory Investigation in River City, a Multi-user Virtual Environment Presenter:
Teaching the Control of Variables Strategy in Fourth Grade Classrooms Robert F. Lorch, Jr., William J. Calderhead, Emily E. Dunlap, Emily C. Hodell, Benjamin.
1/19 Learning with Dynamic Multiple Representations Supporting students in translating between representations in a simulation-based learning environment.
Fostering elementary school students’ understanding of simple electricity by combining simulation and laboratory activities Adviser: Ming-Puu Chen Presenter:
Testing methods that require students to create and answer or develop a product that demonstrates knowledge or skills.
July 8, 2008In vivo experimentation: 1 Step by Step In Vivo Experimentation Lecture 3 for the IV track of the 2011 PSLC Summer School Philip Pavlik Jr.
4:00 – 4:05pm Welcome and Introductions 4:05 – 4:20pm Ice Breaker 4:20-4:30 pm Norms 4:30 – 5:00pm Journaling 5:00 – 5:30 pm Enquiry activity stations.
Thinking aloud about NEW AND OLD BALLS and ramps Bemilies, et al. University of Kentucky--Lexington, KY ABSTRACT INTRODUCTION  Scientists use many methods.
Partnership Beginning-Level Strategic Tutoring Advanced-Level Strategic Tutoring Building Strategic Tutoring Partnerships Partnership Beginning-Level Strategic.
Inquiry-Based Instruction
Preliminary Data Analyses
Oleh: Beni Setiawan, Wahyu Budi Sabtiawan
Evaluation of An Urban Natural Science Initiative
Does Learning from Examples Improve Tutored Problem Solving?
Math Milestones Information Constructed Response
Vincent Aleven & Kirsten Butcher
Welcome to the overview session for the Iowa Core Curriculum
TAKS, Inquiry, Standards and Assessment
Julie Booth, Robert Siegler, Ken Koedinger & Bethany Rittle-Johnson
Learning at the macro level
Presentation transcript:

Comparing Pedagogical Approaches for the Acquisition and Long-Term Robustness of the Control of Variables Strategy By: Michael São Pedro Advisor: Janice Gobert Co-Advisor: Neil Heffernan Sponsors Effectiveness of discovery learning is highly controversial in science education Discovery Learning Open-ended Students ask questions and propose tentative answers Highly unstructured Manipulate objects, perform experiments to confirm their ideas Purported deeper understanding Direct Instruction Clearly established goals Teacher in control of what is learned Highly structured Drill-and-practice of content Better learning gains Probe question Reify Run exp + reify Setup explanation Probe question Setup explanation Construct correct contrast (same as ramp pre/post) Direct + Reify Direct-No Reify Discovery Initial setup Both direct conditions first received initial CVS tutorial. Number of ramp setups controlled in each condition. Pedagogical Approaches Experimental Design Example Questions Overview Showed in Sao Pedro et al. (2009) that two direct instruction variants (with and without reification) significantly outperformed discovery learning on constructing unconfounded experiments starting from an initially multiply confounded experimental setup using a virtual ramp apparatus. Determined robustness of findings by retesting students 6 months after the intervention. We hypothesized direct instruction with reification would show more long-term retention and understanding of CVS than the other conditions. Rationale Inquiry skills can compensate for low science domain knowledge (Hulshof & de Jong, 2006) and may be optimally learned in middle school (Schunn et al. 2007). CVS is a foundational inquiry skill necessary for conducting proper experiments and correctly interpreting data and validating hypotheses. Self-explanation has been found to support deep learning (Chi M. T., 1996) and knowledge integration (Linn & Hsi, 2000). Results Control of Variables Strategy (CVS): a procedure for setting up experimental contrasts such that only one variable is tested and all others are held constant Participants: 57 seventh grade students from a public middle school in central Massachusetts not on IEPs. *Open response items include only those who responded with procedures, not evidential statements. (max = 3) Pre: Pretest Time Direct+ReifyDirect-No ReifyDiscovery Imm: Immediate Posttest Del: Delayed Posttest MeanSDNMeanSDNMeanSDN WPI CVS MultChPre WPI CVS MultChImm WPI CVS MultChDel CVS Explanation*Imm CVS Explanation*Del Strand-Cary ItemsDel Direct Instruction Assessment Direct+Reify and Direct-No Reify students significantly outperformed Discovery on multiply confounded ramp posttest items. Transfer Items No significant differences found between groups on WPI CVS multiple choice, CVS explanations & Strand-Cary transfer items, p> Overall Ramp Performance Collapsing over time, Direct+Reify students construct significantly more unconfounded experiments than both Direct-NoReify and Discovery, p=.014 Though Direct-NoReify has an increase in performance at immediate posttest, there is no significant difference between Direct-NoReify and Discovery when collapsing over time, p>.05 Discovery appears to improve at constructing unconfounded experiments over time. WPI MultCh CVS Ramp Intro Ramp Setups Pretest Immed. Posttest Ramp Setups WPI MultCh CVS CVS Explanation Direct - No Reify Direct + Reify Discovery Interv. Delayed Posttest Ramp Setups WPI + Strand-Cary MultCh CVS CVS Explanation Ramp Re-Intro Last Time….. Now! 2. Singly Confounded Collapsing over time, no significant differences between conditions on mean score, p> Singly Confounded At delayed posttest, mean score was marginally affected by condition, p= Multiply Confounded Collapsing over time, Direct+Reify students made significantly more unconfounded experiments than Discovery (p=.002) and Direct-No reify students (p=.002). 3. Multiply Confounded At the delayed posttest, Direct+Reify made significantly more unconfounded experiments than Direct-No reify (p=.007) and marginally significantly more than Discovery (p=.061) Why teach inquiry? Why the Control of Variables Strategy? Why Reification (Self-Explanation)? US Dept of Ed. R305A NSF-DRL#