Predicting Stag and Hare Hunting Behaviors Using Hidden Markov Model

In this paper, we used Hidden Markov Model (HMM) to describe the gaming behaviors of students and whether they will exhibit “stag” or “hare” hunting behavior in a mobile game for mathematics learning. We found that there is a 99% probability that the students will stay either as stag or hare hunters...

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Main Authors: Bringula, Rex, Rodrigo, Ma. Mercedes T
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Published: Archīum Ateneo 2020
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Online Access:https://archium.ateneo.edu/discs-faculty-pubs/265
https://archium.ateneo.edu/cgi/viewcontent.cgi?article=1266&context=discs-faculty-pubs
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spelling ph-ateneo-arc.discs-faculty-pubs-12662022-03-03T03:28:43Z Predicting Stag and Hare Hunting Behaviors Using Hidden Markov Model Bringula, Rex Rodrigo, Ma. Mercedes T In this paper, we used Hidden Markov Model (HMM) to describe the gaming behaviors of students and whether they will exhibit “stag” or “hare” hunting behavior in a mobile game for mathematics learning. We found that there is a 99% probability that the students will stay either as stag or hare hunters. Our results also suggest that they would choose arithmetic problems involving addition. These game behaviors are not beneficial to learning because they are only exhibiting mathematical skills they already know. The results of the study show that stag and hare hunters have unique traits that separate the one from the other. 2020-01-01T08:00:00Z text application/pdf https://archium.ateneo.edu/discs-faculty-pubs/265 https://archium.ateneo.edu/cgi/viewcontent.cgi?article=1266&context=discs-faculty-pubs Department of Information Systems & Computer Science Faculty Publications Archīum Ateneo collaborative learning game behavior mathematics mobile learning mobile games Computer Sciences Databases and Information Systems Game Design
institution Ateneo De Manila University
building Ateneo De Manila University Library
continent Asia
country Philippines
Philippines
content_provider Ateneo De Manila University Library
collection archium.Ateneo Institutional Repository
topic collaborative learning
game behavior
mathematics
mobile learning
mobile games
Computer Sciences
Databases and Information Systems
Game Design
spellingShingle collaborative learning
game behavior
mathematics
mobile learning
mobile games
Computer Sciences
Databases and Information Systems
Game Design
Bringula, Rex
Rodrigo, Ma. Mercedes T
Predicting Stag and Hare Hunting Behaviors Using Hidden Markov Model
description In this paper, we used Hidden Markov Model (HMM) to describe the gaming behaviors of students and whether they will exhibit “stag” or “hare” hunting behavior in a mobile game for mathematics learning. We found that there is a 99% probability that the students will stay either as stag or hare hunters. Our results also suggest that they would choose arithmetic problems involving addition. These game behaviors are not beneficial to learning because they are only exhibiting mathematical skills they already know. The results of the study show that stag and hare hunters have unique traits that separate the one from the other.
format text
author Bringula, Rex
Rodrigo, Ma. Mercedes T
author_facet Bringula, Rex
Rodrigo, Ma. Mercedes T
author_sort Bringula, Rex
title Predicting Stag and Hare Hunting Behaviors Using Hidden Markov Model
title_short Predicting Stag and Hare Hunting Behaviors Using Hidden Markov Model
title_full Predicting Stag and Hare Hunting Behaviors Using Hidden Markov Model
title_fullStr Predicting Stag and Hare Hunting Behaviors Using Hidden Markov Model
title_full_unstemmed Predicting Stag and Hare Hunting Behaviors Using Hidden Markov Model
title_sort predicting stag and hare hunting behaviors using hidden markov model
publisher Archīum Ateneo
publishDate 2020
url https://archium.ateneo.edu/discs-faculty-pubs/265
https://archium.ateneo.edu/cgi/viewcontent.cgi?article=1266&context=discs-faculty-pubs
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