=Paper=
{{Paper
|id=Vol-1152/paper31
|storemode=property
|title=A Descriptive Study on the Students' Responses to Learning through an On-Line Agricultural Simulation Game
|pdfUrl=https://ceur-ws.org/Vol-1152/paper31.pdf
|volume=Vol-1152
|dblpUrl=https://dblp.org/rec/conf/haicta/OnderSO11
}}
==A Descriptive Study on the Students' Responses to Learning through an On-Line Agricultural Simulation Game==
https://ceur-ws.org/Vol-1152/paper31.pdf
A Descriptive Study on the Students' Responses to
Learning through an On-Line Agricultural Simulation
Game
Hasan Önder1, Kemal Çağatay Selvi2, Sezen Ocak3
1
Department of Animal Science, Faculty of Agriculture, Ondokuz Mayis University,
Samsun – Turkey, e-mail: hasanonder@gmail.com
2
Department of Agricultural Machinery, Faculty of Agriculture, Ondokuz Mayis
University, Samsun – Turkey, e-mail: kcselvi@omu.edu.tr
3
Zirve University, Middle East Sustainable Livestock, Biotechnology and Agro-Ecology
Research and Development Centre, 27260 Gaziantep- Turkey, e-mail:
sezenocak1@gmail.com
Abstract. The purpose of this study is to investigate students’ responses to
learning through an on-line agricultural simulation game. Four hundred and
fifty agricultural engineering students, studying at three different universities
with four grades in Turkey, participated in the study. The data collected from
the questionnaires were analysed by calculating frequencies of responses for
the demographics and multiple-choice questions. To determine the differences
among universities and grades Chi-square statistics were used. The results
reveal that a majority of the surveyed students significantly want to play such a
game at least one hour per day and they thought that it may be useful for their
educational success.
Keywords: Teaching/learning strategies, On-line game, Agricultural
education.
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1 Introduction
Technological developments have been increasingly influencing the
perceptions and conceptualizations of both educators and learners. In recent years,
several attempts have been made to enhance students’ learning experiences by
increasing their motivation, by attempting to focus their attention, and by helping
them to construct more meaningful and permanent records of their learning. In these
attempts, educational computer games gained widespread popularity and acceptance
within educational environments (Karakus at al, 2008). Game-based education and
training for adult learners has a long history with disciplines such as military science,
business and management science, economics, and intercultural communication.
Games and simulations have been played to communicate complex dynamics with
both large and small audiences. Regardless of the media involved, games are aimed
at engendering a variety of cognitive, sensory, and emotional experiences for players
(Raybourn, 2007). Game-based education is the use of computer games to enhance
teaching and learning. Game-based education enables learners to perform tasks and
have experiences which would otherwise be difficult due to cost, time, safety and
other reasons. Nowadays, educational games are adopted by most educational
systems, not only in early age classes, but also in universities (Vasiliou &
Economides, 2007). Both mobile technologies and game technologies are
increasingly seen as fertile ground for the development of resources to support
learning (Facer at al, 2004). Computer games have potential as a learning
environment due to the fact that they can motivate students through entertainment. In
addition, computer games have competitive activities that include rules, goals,
feedback, interaction, and outcomes (Kim at al, 2009). The underlying idea of game
based learning is that students learn better when they are having fun and are engaged
in learning process (Smith & Mann, 2002; Ebner & Holzinger, 2007; Moreno-Ger et
al, 2008).
Computer game skills have been increasingly applied in almost all areas of
human activity within modern societies. As a popular and powerful media, computer
games are being considered for use in educational settings to motivate students, to
focus their attention, and to help them to construct meaningful and permanent records
of their learning. However, before any computer games are adopted for use in an
educational environment, learner analysis should be employed to inform instructors
of the target audience’s expectations, conceptions, and thoughts (Karakus at al,
2008).
The purpose of this study is to investigate students’ responses to learning
through an on-line agricultural simulation game.
2 Methodology
Data collection instruments used in this study includes ten demographics and
eleven multiple choice questions. Open-ended “other” choice was included for each
question. It was aimed in this study to determine 1) whether the students play on-line
games, 2) their education-related expectations from these games, 3) agriculture-
352
related jobs which catch students’ attention, 4) the properties which these games
should have, 5) whether they think that these games can be used in education. A pilot
study was conducted with forty agriculture engineering students, and the questions
were modified for the main study in accordance with these pretest-participants’
responses and comments.
Total of 450 questionnaires were distributed to three agricultural faculties with
four grades, in different cities found in different regions in Turkey. All of the
questionnaires were returned. The questionnaires were administrated by academic
staff of these faculties. Academic staffs provided a guide to implement the
questionnaires properly. They were especially requested not to give clues regarding
the questions and not to interfere in any way with the students’ provision of answers.
The data collected from the questionnaires were analysed by calculating
frequencies of responses for the demographics and multiple-choice questions. To
determine the differences among universities and grades Chi-square statistics were
used (Kim at al, 2009).
3 Results and Discussion
The data In this study, 204 (45.33%) of the participants were in Ondokuz
Mayıs University (OMU) , 126 (28%) of the participants were in Çukurova
University (CU), 120 (26.66%) of the participants were in Kahramanmaraş Sütçü
İmam University (KSU), 162 (36%) of the participants were 1st grade students, 93
(20.66%) of the participants were 2th grade students, 99 (22%) of the participants
were 3th grade students, and 96 (21.33%) of the participants were 4th grade
students.
Rates of Internet use were found significantly high (p<0.01): 18 (4%) students
reported that they do not use and 432 (96%) students reported that they use Internet
in any way. Frequency of Internet use were found as; 117 (27.08%) (at least two
hours daily), 84 (19.44%) (less than two hours in a day), 129 (29.86%) (two days in a
week), 51 (11.81%) (one time in a week) , and 51 (11.81%) (more than a week).
Differences among Internet usage frequency groups were found statistically
significant (p<0.05).
87 (19.33%) students reported that they do not have an e-mail account, 150
(33.33%) students reported that they have an e-mail account, 114 (25.33%) students
reported that they have two e-mail accounts, and 99 (22%) students reported that they
have more than two e-mail accounts (p>0.05).
They were asked how often they play computer games. 135 (30%) students
reported that they do not play computer games, 150 (33.33%) students reported to
rarely play, 102 (22.67%) students reported to often play, and 60 (13.33%) students
reported that they play computer games at least 2 hours per day (p<0.01).
The students were also asked how often they play on-line strategy-simulation
(like Ogame) games. 300 (66.66%) students reported that they do not use on-line
games. 78 (17.33%) students reported to rarely play, 39 (8.67%) students reported to
often play, and 33 (7.33%) students reported that they play computer games at least 2
hour per day (p<0.01).
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The students were asked whether on-line agricultural simulation game could be
useful for their education. 330 (73.33%) students reported that it could be useful, 102
(22.67%) students reported that they were not sure, and 18 (4%) student reported that
it could not be useful (p<0.01). Answers of the students by grades within universities
were given in Table 1.
Table 1. Answers related to usefulness of on-line agricultural simulation game for
education (%)
OMU CU KSU
1 2 3 4 1 2 3 4 1 2 3 4
Y 58.8 36.4 75 81.8 60 70 90.9 72.7 100 90 100 80
NS 38.2 63.6 16.7 9.1 30 30 0 27.3 0 0 0 20
N 2.9 0 8.3 9.1 10 0 9.1 0 0 10 0 0
Y: Yes, NS: Not Sure, N: No
The highest and least rates of “yes” answers were obtained from KSU (92.5%)
and OMU (61.8%), respectively. These differences were found statistically
significant (p<0.05). The highest and the least “not sure” response were found as
33.8% (OMU) and 5% (KSU), respectively (p<0.01). The highest “no” response was
obtained from CU 4.8% and the least “no” response was obtained form KSU 2.5%.
This differences was found statistically significant (p<0.05). These differences were
found statistically insignificant (p>0.05) among universities with all grades. The
other questions were responded only by students who answered this question as
“yes” or “not sure”.
The students were asked how many hours they can spend for this game without
affecting their success on lectures per day. 9 (2.08%) students did not response this
question. 147 (34.03%) students reported that they could spend les than an hour, 210
(48.61%) students reported that they could spend one to two hours, 45 (10.42%)
students reported that they could spend two to three hours, and 21 (4.86%) students
reported that they could spend more than three hours per day. Differences among
these answers were found statistically significant (p<0.01).
The students were asked how often they could visit such a game based learning
system. 9 (2.08%) students did not answer this question. 12 (1.00%), 108 (25.00%),
204 (47.22%) and 99 (22.92%) of the students reported that they visit game based
learning system one time per fifteen days, one time per week, two or three days per
week and every days, respectively. The differences among responses were significant
(p<0.05).
The students were asked which agricultural topics should be in such a game
with multiple choices. Differences among responses were found statistically
significant (p<0.01) (Table 2). Also Table 2 shows the rank of the agricultural topics
belong to universities. Ranks were evaluated by Spearman’s Rank correlation, results
showed that ranks given to the agricultural topics were highly correlated (1.00;
p<0.001) between universities.
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Table 2. The responses on agricultural topic occupation preferences.
Rank
Occupation Number (n) % OMU CU KS
U
Animal rearing 414 95.83 1 1 1
Field crops (wheat etc) 288 66.67 2 2 10
Horticulture (apple etc) 339 78.47 3 3 5
Forages (alfalfa etc) 312 72.22 7 6 3
Agricultural machinery 258 59.72 6 5 7
Agricultural structures 339 78.47 4 4 2
Forestry 93 21.53 14 14 14
Aquaculture 123 28.47 11 12 12
Agricultural cooperatives 150 34.72 10 9 13
Bio-diesel 126 29.17 12 11 11
Artificial insemination 201 46.53 9 10 8
Milk processing 312 72.22 5 7 4
Meat processing 294 68.06 8 8 6
Ornament plants and 171 39.58 13 13 9
landspace
The students were asked which animal species should be in such a game with
multiple choices. Differences among responses were found significant (p<0.01)
(Table 3). Ranks were evaluated by Spearman’s Rank correlation; results showed
that correlations between OMU x CU, OMU x KSU and CU x KSU were 0.852 **,
0.674** and 0.524*, respectively. These correlation coefficients were positive and
statistically significant (**: significant at 1%; *: significant at 5%).
Table 3. The responses on preferences of animal species.
Animal Number (n) %
Dairy cattle 393 90.97
Beef cattle 345 79.86
Goat 294 68.06
Sheep 336 77.78
Hen (laying) 348 80.56
Hen (broiler) 327 75.69
Turkey 114 26.39
Quail 87 20.14
Goose 84 19.44
Duck 90 20.83
Ostrich 198 45.83
Rabbit 102 23.61
Pig 66 15.28
Buffalo 99 22.92
Horse 234 54.17
Fur animals (mink etc) 201 46.53
The students were asked which field crops should be in such a game with
multiple choices. Differences among responses were found significant (p<0.01)
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(Table 4). Ranks were evaluated by Spearman’s Rank correlation; results showed
that correlations between OMU x CU, OMU x KSU and CU x KSU were 0.853 **,
0.433- and 0.412- (**: significant at 1%; -: insignificant at 5%). All these correlation
coefficients were positive but only statistically significant correlation was observed
between OMU x CU. The students of KSU prefer the different field crops such as oat
and colza while students of OMU and CU prefer maize and beetroots.
Table 4. Student responses on field crop preferences.
Field crops Number (n) %
Wheat 405 93.75
Barley 369 85.42
Colza 198 45.83
Rye 258 59.72
Oats 285 65.97
Triticale 129 29.86
Corn (grain) 357 82.64
Corn (ensiled) 255 59.03
Potatoes 195 45.14
Tobacco 144 33.33
Cotton 276 63.89
Sunflower 288 66.67
Soybean 189 43.75
Lentil 168 38.89
Chickpea 213 49.31
Sugar beet 225 52.09
Broad beans 168 38.89
The students were also asked which forages should be in such a game with
multiple choice. 402 (93.06%) of the students reported that alfalfa, 297 (68.75%) of
the students reported that sainfoin, and 345 (79.86%) of the students reported that
pasture grass should be in the game. Differences among these crops were found
insignificant (p>0.05).
The students were asked which horticultural plants should be in such a game
with multiple choices. Differences among responses were found significant (p<0.01)
for horticultural plants (Table 5). Ranks were evaluated by Spearman’s Rank
correlation; results showed that correlations between OMU x CU, OMU x KSU and
CU x KSU were 0.896**, 0.343- and 0.359- (**: significant at 1%; -: insignificant at
5%). All these correlation coefficients were positive but only statistically significant
correlation was observed between OMU x CU. The students of KSU prefer the
different horticultural plants such as walnut while students of OMU and CU prefer
apple and grape. These differences should be originated from the regional
agricultural production style.
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Table 5. The responses on horticultural plant preferences.
Plants Number (n) %
Apple 372 86.11
Pear 270 62.50
Peach 273 63.19
Apricot 198 45.83
Grape 303 70.14
Cherry 297 68.75
Plum 150 34.72
Hazelnut 219 50.69
Walnut 252 58.33
Olive 279 64.58
Strawberry 249 57.64
Vegetable (tomato, pepper etc.) 294 68.06
The other traits were not evaluated by Spearman’s Rank correlation because of
insufficient sample size to avoid statistical errors.
They were asked that how much the animal houses and agricultural structures
should be detailed. 27 (6.25%) of the students did not answer this question, 9
(2.08%) students reported that animal houses and structures should not be detailed,
84 (19.45%) students reported that they should be detailed but not much, and 312
(%72.22) students reported that they should be more detailed that player could affect
all items in the building such as amount of trough and water bowls. Differences
among preferences were found significant (p<0.01).
They were also asked how much agricultural machines should be detailed. 15
(3.47%) students did not answer this question, 15 (3.47%) students reported that
agricultural machines should not be detailed, 177 (40.97%) students reported that
agricultural machines should be detailed, and 225 (52.09%) students reported that
agricultural machines should be more detailed such as fuel consumption, breaking
down etc. Differences among preferences were found significant (p<0.01).
The students were asked to how cooperatives should work in such a game. 18
(4.17%) of the students did not answer this question, 96 (22.22%) students reported
that cooperatives should be managed by the computer system and 318 (73.61%)
students reported that cooperatives should be directed by players for buying and
selling equipments and goods. Differences among preferences were found significant
(p<0.01).
The students were asked whether fertilizers and treatments should be detailed in
such a game. 12 (2.78%) of the students did not answer this question, 366 (84.72%)
students reported as “YES” and 54 (12.50%) students reported as “NO”. Differences
among preferences were found significant (p<0.01).
They were also asked to how rations should be given to the animals. All the
students answered this question. 396 (91.67%) and 36 (8.33%) students reported that
rations should be prepared by players and fixed rations should be used, respectively.
Differences between preferences were found statistically significant (p<0.01).
As a last question, they were asked whether they play such a game. All the
students answered this question. 408 (94.44%) of the students reported that they
357
would want to play and 24 (5.56%) of the students reported that they would not want
to play. Differences between preferences were found significant (p<0.01).
4 Conclusion
It was aimed to investigate students’ responses to learning through an on-line
agricultural simulation game. The results reveal that a majority of the surveyed
students significantly want to play such a game at least one hour per day without
affecting their success on their lectures and they thought that it may be useful for
their education.
Preferences on agricultural topics of surveyed students showed that they mostly
interested on animal rearing, horticulture, field crops, agricultural structures, milk
and meat processing, forages, and agricultural machinery. According to this some
topics such as forestry could be eliminated from such a game.
Surveyed students mostly interested on dairy and beef cattle, hens, sheep and
goats. Preferences on pig rearing is quite small, it must be the cause of religion. For
the field crops, they mostly interested on wheat, barley, oats, cotton and sunflower.
In terms of horticulture they interested on apple, grape, olive, vegetables, peach and
pear.
For the other agricultural areas such as agricultural equipments and structures
they wanted detailed properties.
Most of the students (94.44%) declared that they want to play such a game to
help their education on agricultural engineering.
When the on-line agricultural simulation game is prepared, findings mentioned
above should be taken into consideration.
Acknowledgements
Authors thank to Dr. Mustafa Boğa (Çukurova University) and Dr. Mustafa
Şahin (Kahramanmaraş Sütçü İmam University) for their efforts during the
administration of the survey. Also, we wish to thank Dr. Ali Vaiz Garipoğlu, for his
help with language correction of the manuscript.
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