At present, environmental issues are of concern to all countries, especially for developing countries, and education on waste sorting is urgent. However, it remains a challenge to improve students’ learning achievement and engagement in environmental education. Researchers have pointed out the potential of digital games for promoting students’ learning motivation. In addition, the two-tier testing mechanism has been recognized as an effective tool for correcting students’ misconceptions and promoting their in-depth thinking. Therefore, this study proposed a two-tier testing-based digital gaming approach. To verify the effectiveness of the approach, a digital game was developed and a quasi-experiment was conducted. The participants were two classes of fifth graders, with one class as the experimental group using the two-tier test-based digital game and the other class as the control group learning with the conventional digital game. The results showed that the digital game-based learning with two-tier testing model was conducive to students' improved academic performance compared with the conventional digital game-based learning model, especially for students in the low-level group, who were able to make greater progress. In addition, the approach was effective in terms of reducing students’ cognitive load and improving their flow experience.
AdmiraalW.HuizengaJ.AkkermanS.DamG. T. (2011). The concept of flow in collaborative game-based learning. Computers in Human Behavior, 27(3), 1185–1194. https://doi.org/10.1016/j.chb.2010.12.013
2.
BellottiF.KapralosB.LeeK.Moreno-GerP.BertaR. (2013). Assessment in and of serious games: An overview. Advances in Human-Computer Interaction, 2013. https://doi.org/10.1155/2013/136864
3.
BruceR. W. (1933). Conditions of transfer of training. Journal of Experimental Psychology, 16(3), 343–361. https://doi.org/10.1037/h0074550
CarpenterS. K.DeLoshE. L. (2006). Impoverished cue support enhances subsequent retention: Support for the elaborative retrieval explanation of the testing effect. Memory & Cognition, 34(2), 268–276. https://doi.org/10.3758/bf03193405
6.
CarrierM.PashlerH. (1992). The influence of retrieval on retention. Memory & Cognition, 20(6), 633–642. https://doi.org/10.3758/BF03202713
7.
ChandlerP.SwellerJ. (1991). Cognitive load theory and the format of instruction. Cognition and Instruction, 8(4), 293–332. https://doi.org/10.1207/s1532690xci0804_2
8.
ChangS. C.HsuT. C.KuoW. C.JongM. S. Y. (2020). Effects of applying a VR‐based two‐tier test strategy to promote elementary students’ learning performance in a geology class. British Journal of Educational Technology, 51(1), 148–165. https://doi.org/10.1111/bjet.12790
9.
ChangC. C.WardenC. A.LiangC.LinG. Y. (2018). Effects of digital game-based learning on achievement, flow and overall cognitive load. Australasian Journal of Educational Technology, 34(4). https://doi.org/10.14742/ajet.2961
10.
CharskyD.ResslerW. (2011). “Games are made for fun”: Lessons on the effects of concept maps in the classroom use of computer games. Computers & Education, 56(3), 604–615. https://doi.org/10.1016/j.compedu.2010.10.001
11.
ChenH.WigandR. T.NilanM. (2000). Exploring web users’ optimal flow experiences. Information Technology & People, 13(4), 263–281. https://doi.org/10.1108/09593840010359473
12.
ChuH.-C.ChangS.-C. (2014). Developing an educational computer game for migratory bird identification based on a two-tier test approach. Educational Technology Research and Development, 62(2), 147–161. https://doi.org/10.1007/s11423-013-9323-4
13.
ChuH.-C.HwangG.-J.TsaiC.-C.TsengJ. C. R. (2010). A two-tier test approach to developing location-aware mobile learning systems for natural science courses. Computers & Education, 55(4), 1618–1627. https://doi.org/10.1016/j.compedu.2010.07.004
14.
ÇilE. (2015). Effect of two-tier diagnostic tests on promoting learners’ conceptual understanding of variables in conducting scientific experiments. Applied Measurement in Education, 28(4), 253–273. https://doi.org/10.1080/08957347.2015.1064124
15.
CohenJ. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Earlbaum Associates. https://doi.org/10.4324/9780203771587
16.
ConnollyT. M.BoyleE. A.MacArthurE.HaineyT.BoyleJ. M. (2012). A systematic literature review of empirical evidence on computer games and serious games. Computers & Education, 59(2), 661–686. https://doi.org/10.1016/j.compedu.2012.03.004
17.
CsikszentmihalyiM. (1997). Flow and the psychology of discovery and invention (p. 39). HarperPerennial.
18.
CsikszentmihalyiM. (2000). Beyond boredom and anxiety. Jossey-Bass.
19.
CsikszentmihalyiM.CsikzentmihalyM. (1990). Flow: The psychology of optimal experience (1990). Harper & Row.
20.
EllisH. C. (1965). The transfer of learning. New York: MacMillan.
21.
ErhelS.JametE. (2013). Digital game-based learning: Impact of instructions and feedback on motivation and learning effectiveness. Computers & Education, 67, 156–167. https://doi.org/10.1016/j.compedu.2013.02.019
22.
GirardC.EcalleJ.MagnanA. (2013). Serious games as new educational tools: How effective are they? A meta‐analysis of recent studies. Journal of Computer Assisted Learning, 29(3), 207–219. https://doi.org/10.1111/j.1365-2729.2012.00489.x
23.
HawlitschekA.JoeckelS. (2017). Increasing the effectiveness of digital educational games: The effects of a learning instruction on students’ learning, motivation and cognitive load. Computers in Human Behavior, 72, 79–86. https://doi.org/10.1016/j.chb.2017.01.040
24.
HsuC. Y.TsaiC. C.WangH. Y. (2012). Facilitating third graders’ acquisition of scientific concepts through digital game-based learning: The effects of self-explanation principles. The Asia-Pacific Education Researcher, 21(1), 71–82.
25.
HwangG.-J.SungH.-Y.HungC.-M.HuangI.TsaiC.-C. (2012). Development of a personalized educational computer game based on students’ learning styles. Educational Technology Research and Development, 60(4), 623–638. https://doi.org/10.1007/s11423-012-9241-x
26.
HwangG.-J.WuP.-H.ChenC.-C. (2012). An online game approach for improving students’ learning performance in web-based problem-solving activities. Computers & Education, 59(4), 1246–1256. https://doi.org/10.1016/j.compedu.2012.05.009
27.
HwangG. J.WuP. H.ZhuangY. Y.HuangY. M. (2013). Effects of the inquiry-based mobile learning model on the cognitive load and learning achievement of students. Interactive Learning Environments, 21(4), 338–354. https://doi.org/10.1080/10494820.2011.575789
28.
HwangG.-J.YangL.-H.WangS.-Y. (2013). A concept map-embedded educational computer game for improving students’ learning performance in natural science courses. Computers & Education, 69, 121–130. https://doi.org/10.1016/j.compedu.2013.07.008
LiaoC.-W.ChenC.-H.ShihS.-J. (2019). The interactivity of video and collaboration for learning achievement, intrinsic motivation, cognitive load, and behavior patterns in a digital game-based learning environment. Computers & Education, 133(2), 43–55. https://doi.org/10.1016/j.compedu.2019.01.013
31.
LiX.BiF.HanZ.QinY.WangH.WuW. (2019). Garbage source classification performance, impact factor, and management strategy in rural areas of China: A case study in Hangzhou. Waste Management, 89(10), 313–321. https://doi.org/10.1016/j.wasman.2019.04.020
32.
LiF.-Y.HwangG.-J.ChenP.-Y.LinY.-J. (2021). Effects of a concept mapping-based two-tier test strategy on students’ digital game-based learning performances and behavioral patterns. Computers & Education, 173, 104293. https://doi.org/10.1016/j.compedu.2021.104293
33.
LiR.MengZ.TianM.ZhangZ.XiaoW. (2019). Modelling Chinese efl learners’ flow experiences in digital game-based vocabulary learning: The roles of learner and contextual factors. Computer Assisted Language Learning, 34(1), 1–22. https://doi.org/10.1080/09588221.2019.1619585
34.
MavridisA.TsiatsosT. (2017). Game‐based assessment: Investigating the impact on test anxiety and exam performance. Journal of Computer Assisted Learning, 33(2), 137–150. https://doi.org/10.1111/jcal.12170
35.
McClellandJ. L.RumelhartD. E. (1985). Distributed memory and the representation of general and specific information. Journal of Experimental Psychology. General, 114(2), 159–197. https://doi.org/10.1037/0096-3445.114.2.159
36.
MutluA.SesenB. A. (2015). Development of a two-tier diagnostic test to assess undergraduates’ understanding of some chemistry concepts. Procedia-Social and Behavioral Sciences, 174, 629–635. https://doi.org/10.1016/j.sbspro.2015.01.593
37.
NinausM.MoellerK.McMullenJ.KiiliK. (2017). Acceptance of game-based learning and intrinsic motivation as predictors for learning success and flow experience. International Journal of Serious Games, 4(3). https://doi.org/10.17083/ijsg.v4i3.176
38.
PaasF. G. (1992). Training strategies for attaining transfer of problem-solving skill in statistics: A cognitive-load approach. Journal of educational psychology, 84(4), 429–434. https://doi.org/10.1037/0022-0663.84.4.429
39.
PaasF.RenklA.SwellerJ. (2003). Cognitive load theory and instructional design: Recent developments. Educational Psychologist, 38(1), 1–4. https://doi.org/10.1207/S15326985EP3801_1
40.
PapastergiouM. (2009). Digital game-based learning in high school computer science education: Impact on educational effectiveness and student motivation. Computers & Education, 52(1), 1–12. https://doi.org/10.1016/j.compedu.2008.06.004
PengH.ShenN.YingH.WangQ. (2021). Factor analysis and policy simulation of domestic waste classification behavior based on a multiagent study—Taking Shanghai’s garbage classification as an example. Environmental Impact Assessment Review, 89, 106598. https://doi.org/10.1016/j.eiar.2021.106598
43.
RegadíoM.RuizA. I.Rodríguez-RastreroM.CuevasJ. (2015). Containment and attenuating layers: An affordable strategy that preserves soil and water from landfill pollution. Waste Management, 46, 408–419. https://doi.org/10.1016/j.wasman.2015.08.014
44.
SchraderC.BastiaensT. J. (2012). The influence of virtual presence: Effects on experienced cognitive load and learning outcomes in educational computer games. Computers in Human Behavior, 28(2), 648–658. https://doi.org/10.1016/j.chb.2011.11.011
45.
Shapiro-BengtsenS.AndersenF. M.MünsterM.ZouL. (2020). Municipal solid waste available to the Chinese energy sector–provincial projections to 2050. Waste Management, 112, 52–65. https://doi.org/10.1016/j.wasman.2020.05.014
46.
SwellerJ.Van MerrienboerJ. J. G.PaasF. G. W. C. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10(3), 251–296. https://doi.org/10.1023/A:1022193728205
47.
TapingkaeP.PanjabureeP.HwangG.-J.SrisawasdiN. (2020). Effects of a formative assessment-based contextual gaming approach on students’ digital citizenship behaviours, learning motivations, and perceptions. Computers & Education, 159, 103998. https://doi.org/10.1016/j.compedu.2020.103998
48.
TaubM.SawyerR.SmithA.RoweJ.AzevedoR.LesterJ. (2020). The agency effect: The impact of student agency on learning, emotions, and problem-solving behaviors in a game-based learning environment. Computers & Education, 147, 103781. https://doi.org/10.1016/j.compedu.2019.103781
49.
TreagustD. F. (1988). Development and use of diagnostic tests to evaluate students’ misconceptions in science. International Journal of Science Education, 10(2), 159–169. https://doi.org/10.1080/0950069880100204
50.
TsaiC.-C. (2001). The interpretation construction design model for teaching science and its applications to internet-based instruction in Taiwan. International Journal of Educational Development, 21(5), 401–415. https://doi.org/10.1016/S0738-0593(00)00038-9
51.
TsaiC.-C. (2003). Using a conflict map as an instructional tool to change student alternative conceptions in simple series electric-circuits. International Journal of Science Education, 25(3), 307–327. https://doi.org/10.1080/09500690210145756
TsangP. S.VelazquezV. L. (1996). Diagnosticity and multidimensional subjective workload ratings. Ergonomics, 39(3), 358–381. https://doi.org/10.1080/00140139608964470
54.
WangT.-H. (2014). Developing an assessment-centered e-learning system for improving student learning effectiveness. Computers & Education, 73, 189–203. https://doi.org/10.1016/j.compedu.2013.12.002
55.
YangK.-H. (2017). Learning behavior and achievement analysis of a digital game-based learning approach integrating mastery learning theory and different feedback models. Interactive Learning Environments, 25(2), 235–248. https://doi.org/10.1080/10494820.2017.1286099
56.
YangQ.-F.ChangS.-C.HwangG.-J.ZouD. (2020). Balancing cognitive complexity and gaming level: Effects of a cognitive complexity-based competition game on EFL students’ English vocabulary learning performance, anxiety and behaviors. Computers & Education, 148, 103808. https://doi.org/10.1016/j.compedu.2020.103808
57.
YangT.-C.ChenS. Y.HwangG.-J. (2015). The influences of a two-tier test strategy on student learning: A lag sequential analysis approach. Computers & Education, 82, 366–377. https://doi.org/10.1016/j.compedu.2014.11.021
58.
YangK.-H.LuB.-C. (2021). Towards the successful game-based learning: Detection and feedback to misconceptions is the key. Computers & Education, 160, 104033. https://doi.org/10.1016/j.compedu.2020.104033
59.
ZhangB.LaiK. H.WangB.WangZ. (2019). From intention to action: How do personal attitudes, facilities accessibility, and government stimulus matter for household waste sorting?Journal of Environmental Management, 233, 447–458. https://doi.org/10.1016/j.jenvman.2018.12.059
60.
ZouD.ZhangR.XieH.WangF. L. (2021). Digital game-based learning of information literacy: Effects of gameplay modes on university students’ learning performance, motivation, self-efficacy and flow experiences. Australasian Journal of Educational Technology, 37(2), 152–170. https://doi.org/10.14742/ajet.6682
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