IEEE Systems, Man and Cybernetics Magazine - January 2021 - 18

Breznitz and Nevat [25]. It presents a phrase to the user, and
the text starts to disappear letter by letter from the beginning. After the text has totally disappeared or the user has
signaled that he/she has finished reading, a four-choice comprehension question is presented to the user. Depending on
the answer, the text-fading speed will be increased or
decreased. This keeps the users on the edge of their reading
rate and pushes them to read the phrases faster.
Finally, the reading task in the vocabulary module is a
cloze question called accelerated word meaning recognition (AWMR). It represents a phrase with one word missing, and the user has to select the appropriate word and
ignore the distractors. This task is also designed to both
improve the vocabulary of the user as well as increase the
automaticity in word decoding and sentence reading.
The Gamification of the Reading Tasks
Learning to read can be a hard and laborious task, especially when a child is underachieving and feeling the pressure of lagging behind. Having difficulty in learning to
read can lead to demotivation and discouragement for
engaging in reading activities, and this can further widen
the gap between achieving and underachieving readers
[26]-[28]. For poor readers, reading activities by themselves do not induce enough motivation to encourage persistence and adherence in children, and instructors need
to target both reading skills and motivation [29]. Hence,
that is why gamification is proposed as a mechanism to
increase motivation, engagement, and persistence in the
process of reading acquisition.
Gamification has been defined as " using game design
elements in nongaming context " [30]. It has been shown to
make school lessons more interesting and motivating for
the students [31]. It can positively affect the learner's attitude and behavior toward learning tasks [32]. In addition,
it can be used to improve the learner's engagement [33],
[34] as well as their autonomy and creativity [35]. In addition, it is found that, despite increasing cognitive load, it
can lead to higher achievement among students [36].
Through the use of gamification principles, the four
reading tasks designed for this system were transformed
into four minigames. A thematic was chosen for all the
minigames to make them look coherent. As the system targets young children, this thematic was chosen to be the
four holidays of Christmas (AWD), Halloween (AWMR),
Easter (APR), and Thanksgiving (AWSR). Various game
elements were incorporated into this gamified system. To
summarize, they cover reinforcements (continuous, intermittent, and variable as well as positive and negative),
goals and progress bars (proximal and distal), feedback
(immediate, concurrent, and corrective), and finally,
scores, levels, and leaderboards (micro and macro). In
addition, motivation theories such as self-efficacy (mastery experience, vicarious experience, and verbal persuasion) and self-determination (autonomy, competence, and
relatedness) [37]-[39] were used as guidelines to design
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IEEE SYSTEMS, MAN, & CYBERNETICS MAGAZINE Janu ar y 2021

the gamified system. The architecture of the system is
found in Figure 1.
The Optimization Model
of the Intelligent Instruction
The process of skill acquisition should be adapted to one's
individual needs and characteristics. If the training task is
too difficult, it will produce frustration, and if the task is
too easy, it could become boring to the user [7], [40].
According to the flow theory [7], the balance between
skills and challenges is the key to increasing motivation
and focus. In real learning processes, normally, it is the
role of a teacher or a tutor to determine the appropriate
educational content and its suited difficulty level. The
teacher should offer the educational content that provides
the most value and make sure that the tasks remain challenging without making them too difficult.
For designing an instructional tool dedicated to home
use, it has to be sufficiently intelligent to eliminate the
requirement of a teacher's intervention. Maximizing
theĀ  educational value of a training session while keeping
the difficulty level of the session below the abilities of the
learner is an optimization problem. The knapsack problem
is an optimization method used in previous research on
education; it is appropriate for modeling the reading
instructional tasks presented in this article [41]. In the
knapsack problem, for a given set of items, each with a
weight and value, we should choose the items that offer
the best total value while not surpassing the weight limit.
In the context of a reading program, every word or question has a certain weight that is defined by its level of difficulty. The more difficult words will have higher weights.
Then, each word or question should have a certain value.
Since the objective function of the knapsack is to maximize the total value of the selected items, an item with a
higher value has a greater chance of being selected.
The constraint about the difficulty of the selected
items makes sure that the set of selected items (words or
questions) respect the defined weight limit. This model
includes an upper weight (UW) for the upper limit and a
lower weight (LW) for the lower limit. The UW limits the
difficulty of the content to avoid frustration, and the LW
limits its ease to avoid being boring. An additional constraint maintains the number of selected items within
the defined boundaries. In this model, the upper number
(UN) is the upper limit on the maximum number of items
that can be selected, and the lower number (LN) is the
lower limit. The objective of this constraint is to make
the amount of the content of the sessions uniform;
hence, the sessions are all the same length. The third
constraint limits the number of presentations (P) for
each word or question to a fixed maximum value so that
no words or questions would be presented more than
that maximum.
The starting value of each word was derived from the frequency of the word in the language (retrieved from Wordnik



IEEE Systems, Man and Cybernetics Magazine - January 2021

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