Please Join the Kaggle-Grockit Competition: "What Do You Know"

Grockit, https://grockit.com/, is an online social-learning company. Grockit prepares students for the SAT, ACT, GMAT, LSAT and GRE standardized exams, and administer practice tests online. Grockit has made available, through Kaggle, a database containing the response strings of 179,106 users (students) responding to 6,045 questions (test items) from practice tests for the ACT (with subtests: English, Math, Reading, Science), SAT (Math, Reading, Writing) and GMAT (Quantitative, Verbal). Each student has responded to between 1 and 2,352 questions. Each question has been answered by between 2 and 14,063 users. The dataset has 4,851,475 reported responses, so that there are 99.6% missing responses. Grockit has also supplied information about each of the questions, such as its subtest, and also about each of the user's responses, such as its start and finish times.

There are a further 93,100 responses in the database with user and question information, but with blanked out responses. The challenge from Grockit is to predict which of those responses were correct and which were incorrect. For each of those responses, competitors submit the probability that the response was correct. Competitors are allowed to submit two sets of 93,100 response-probabilities each day until the competition ends on 29 February, 2012. Please join the competition at the Kaggle website:

http://www.kaggle.com/c/WhatDoYouKnow.

Kaggle have done their own analysis of this dataset, and have reported the Binomial Capped Deviance, BCD, of its set of predictions as the "LMER Benchmark". They used a random-effects Rasch model implemented with the LMER package of the R-Statistics software. This Benchmark analysis is surprisingly effective, producing a better BCD than a simple run of Winsteps or Facets. As of 12/18/2011, the leading submission appears to predict about 65% successfully. It is not known what technique was used to create that submission.

The Grockit data also reveal aspects of students' behavior. Figure 1 shows how long after an item is displayed on the computer's screen that the student responds. The logarithmic curve is close to linear, but with two steps. This suggests that there may be a time-out mechanism at work. Figure 2 shows the correctness of the responses in Figure 1. Again we can speculate about what mechanisms are at work.

John Michael Linacre


Figure 1. Response times for valid scored responses in the Grockit-Kaggle database

Figure 2. Percentage of correct responses at different response times for valid scored responses in the Grockit-Kaggle database.


Please Join the Kaggle-Grockit Competition: "What Do You Know", John M. Linacre . ... Rasch Measurement Transactions, 2011, 25:3, 1329


Please help with Standard Dataset 4: Andrich Rating Scale Model



Rasch Publications
Rasch Measurement Transactions (free, online) Rasch Measurement research papers (free, online) Probabilistic Models for Some Intelligence and Attainment Tests, Georg Rasch Applying the Rasch Model 3rd. Ed., Bond & Fox Best Test Design, Wright & Stone
Rating Scale Analysis, Wright & Masters Introduction to Rasch Measurement, E. Smith & R. Smith Introduction to Many-Facet Rasch Measurement, Thomas Eckes Invariant Measurement: Using Rasch Models in the Social, Behavioral, and Health Sciences, George Engelhard, Jr. Statistical Analyses for Language Testers, Rita Green
Rasch Models: Foundations, Recent Developments, and Applications, Fischer & Molenaar Journal of Applied Measurement Rasch models for measurement, David Andrich Constructing Measures, Mark Wilson Rasch Analysis in the Human Sciences, Boone, Stave, Yale
in Spanish: Análisis de Rasch para todos, Agustín Tristán Mediciones, Posicionamientos y Diagnósticos Competitivos, Juan Ramón Oreja Rodríguez

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