Multinomial processing tree models

Results 21 to 30 of about 10,130,111 (108)

Improving the measurement of knowledge in multiple-choice tests: A hierarchical multinomial processing tree approach

Acta Psychologica
In multiple-choice (MC) tests, correct item responses can stem from actual mastery as well as from lucky guessing. Several approaches have been developed to address this problem, including the implementation of a “Don't know” option.
Timo Seitz, Franziska M. Leipold, Julius Protte +2 more
doaj +1 more source

Sequential Hypothesis Tests for Multinomial Processing Tree Models

, 2019
All R scripts and simulation data for the manuscript "Sequential Hypothesis Tests in Multinomial Processing Tree Models" (Schnuerch, Erdfelder, & Heck, 2019)
Martin Schnuerch, Daniel W. Heck, Edgar Erdfelder +2 more
core +2 more sources

How to develop, test, and extend multinomial processing tree models: A tutorial

, 2023
Supplementary material for: Tutorial on multinomial processing tree modeling: How to develop, test, and extend MPT models (Schmidt, Erdfelder, & Heck ...
Oliver Schmidt +5 more
core +1 more source

Multinomial Logit Models with Implicit Variable Selection [PDF]

, 2010
Multinomial logit models which are most commonly used for the modeling of unordered multi-category responses are typically restricted to the use of few predictors. In the high-dimensional case maximum likelihood estimates frequently do not exist. In this
Tutz, Gerhard, Zahid, Faisal Maqbool
core +1 more source

Representing Probabilistic Models of Knowledge Space Theory by Multinomial Processing Tree Models

, 2020
Supplementary material for the manuscript "Representing Probabilistic Models of Knowledge Space Theory by Multinomial Processing Tree ...
Stefano Noventa, Daniel W. Heck
core +1 more source

Opinion mining using ensemble model for restaurant feedback analysis

Discover Computing
The research work introduces a new method for sentiment analysis in the context of restaurant evaluations, emphasizing the optimization of the trade-off between processing time and accuracy.
Rohan S. Kamath, M. R. Kaushik, M. Ramakrishna +2 more
doaj +1 more source

Is Deliberate Control of Behavior Rare? A Test of the Automaticity Dominance Perspective

Socius
The “automaticity dominance” perspective on cognition and behavior holds that automatic processes guide most behavior because deliberate processing is slow, inefficient, and therefore rare, typically restricted to “problematic” situations. Other scholars
Andrew Miles, Salwa Khan, Yagana Samim
doaj +1 more source

Implementation of Lightweight Machine Learning Models for Real-time Text Classification on Resource-Constrained Devices

Journal of Informatics and Web Engineering
This paper addresses the growing need for implementing intelligent Natural Language Processing (NLP) systems on low-power, memory-limited devices such as Raspberry Pi, mobile phones, and IoT edge hardware. As edge computing and smart devices proliferate,
Marwah Zaid Mohammed Al-Helali, Naveen Palanichamy, K. Revathi +2 more
doaj +1 more source

Supervised Machine Learning-Based Multiclass Classification and Interpretable Feature Importance Analysis of Teacher Job Satisfaction

Information
This study examines the increasing concern regarding teacher job satisfaction, which has a direct impact on retention, instructional quality, and student outcomes.
Bouabid Qabliyane +4 more
doaj +1 more source

Source memory and collaborative learning: the roles of conflicting information, group composition, and learning partner expertise

Frontiers in Education
IntroductionAfter collaborative learning, remembering which learning partner shared certain information (source memory) supports social learning strategies such as academic help-seeking: remembering the source helps to ask the right peer when further ...
Oktay Ülker, Daniel Bodemer
doaj +1 more source

machine learning
recognition heuristic