Error Analysis as a Validation of Learning Progressions

نویسندگان

  • Brent Morgan
  • William Baggett
  • Vasile Rus
چکیده

Learning progressions (LPs) are a recent educational theory pertaining to student modeling. LPs argue that students with equal test scores may nonetheless have different conceptualizations of the material, with varying degrees of maturity. However, there is little empirical validation for LPs. To this end, we mapped two physics LPs (one predefined, one described in the paper) onto the answer choices of a popular conceptual physics test (the Force Concept Inventory; FCI). We then assessed 444 high school physics students using a pretest-posttest design. Students with more mature incorrect answers on the pretest performed better on the posttest than their less mature counterparts. We discuss implications for theorists and practitioners in learner modeling.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Application of ensemble learning techniques to model the atmospheric concentration of SO2

In view of pollution prediction modeling, the study adopts homogenous (random forest, bagging, and additive regression) and heterogeneous (voting) ensemble classifiers to predict the atmospheric concentration of Sulphur dioxide. For model validation, results were compared against widely known single base classifiers such as support vector machine, multilayer perceptron, linear regression and re...

متن کامل

Modeling Discharge Coefficient of Side Weir on Converging Channel Using Extreme Learning Machine

In this study, the discharge coefficient of side weirs located on converging channels was simulated for the first time using a new method of Extreme Learning Machine (ELM). To examine the accuracy of the numerical model, the Monte Carlo simulations were used and the experimental values validation was conducted by the k-fold cross validation method. Then, the input parameters were detected for s...

متن کامل

Cystoscopy Image Classication Using Deep Convolutional Neural Networks

In the past three decades, the use of smart methods in medical diagnostic systems has attractedthe attention of many researchers. However, no smart activity has been provided in the eld ofmedical image processing for diagnosis of bladder cancer through cystoscopy images despite the highprevalence in the world. In this paper, two well-known convolutional neural networks (CNNs) ...

متن کامل

Exploring Impacts of Consciousness-raising in a Genre-based Pedagogy

This study reports on the findings of a genre teaching course for developing academic writing of a class of EFL students in Iran. The information report genre was taught in a cyclical way of teaching and learning, which was started from ‘setting the context’ and ‘deconstruction’ of prototype information report genre, and continued with ‘joint construction’, ‘independent construction’, and final...

متن کامل

Machine Learning Models for Housing Prices Forecasting using Registration Data

This article has been compiled to identify the best model of housing price forecasting using machine learning methods with maximum accuracy and minimum error. Five important machine learning algorithms are used to predict housing prices, including Nearest Neighbor Regression Algorithm (KNNR), Support Vector Regression Algorithm (SVR), Random Forest Regression Algorithm (RFR), Extreme Gradient B...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2014