Compared with students with low flow, students with medium
flow were reinforced by the sequence of trial-and-error behaviors
in the analyzing phase (A?F), and they had none of the repeated
incorrect manipulations that students with low flow exhibited.
Although lacking in the ‘IM?A’ reflective process, compared with
the students in the low-flow group, those from the medium group
did not exhibit repeated incorrect manipulations that may have
affected their involvement in the game. Unlike the other two
groups, the students from the high-flow group were enhanced by
the reflective process of ‘IM?A’, indicating that they tended to
return to analyzing in a timely manner after incorrect manipulations.
In addition, the high-flow group did not show pattern of
‘restarting after analyzing’ (A?R), which indicated a deeper
immersion with a greater tendency toward the interactive processes
of manipulation and analysis. This suggests that unless they
failed during the analyzing phase, they were less likely to give up
the game and restart immediately after the analysis. They tended
to emphasize a more continuous and smooth problem-solving
strategy, which may have facilitated their complete experience of
the context, the clues, and procedural knowledge.
Compared to traditional teaching methods, the use of simulation
software in science or engineering courses can better promote
learners’ participation and satisfaction (Duran, Gallardo, Toral,
Martinez-Torres, & Barrero, 2007). Additionally, merging the challenging
and entertaining features of simulation games with
simulation software in science education games should help
improve learners’ degree of immersion. To assess students’ immersion
in simulation games, flow is an important and influential indicator
(Bressler & Bodzin, 2013). The above analyses indicate that
the students’ average flow score in the simulation game activities
was greater than the median flow score, demonstrating the game’s
positive effects on students’ learning motivation and immersion. In
addition, regarding the reflective behavior processes of students
with different levels of flow, our analysis also revealed a connection
between students’ flow and their reflective behavior processes:
the learners with higher flow states displayed more complete
and in-depth reflective behavior patterns. Therefore, designing
simulation games that are capable of elevating learners’ flow state
may help to enhance their reflection on scientific knowledge.
Because previous studies have observed that appropriate challenges
and clear goals in simulation games can have a significant
influence on learners’ flow state (Hou & Li, 2014), to promote learners’
flow experience and reach a more in-depth and complete
reflective process, the games must be designed with clear goals
to fully correspond to the learning objectives. Moreover, the scaffolding
provided by the simulation games in science education
should consider learners’ prior knowledge and include a variety
of timely guidance and context features to promote concentration and the completion of students’ reflective process.