Christopher Griffiths

Judy Bowen
email: jbowen@waikato.ac.nz

Annika Hinze
email: hinze@waikato.ac.nz

Investigating Wearable Technology for Fatigue Identification in the Workplace

Fatigue has been identified as a significant contributor to workplace accident rates. However, risk minimisation is a process largely based on selfreporting methodologies, which are not suitable for fatigue identification in high risk industries. Wearable technology which is capable of collecting physiological data such as step and heart rates as an individual performs workplace tasks has been proposed as a possible solution. Such devices are minimally intrusive to the individual and so can be used throughout the working day. Much is promised by the providers of such technology, but it is unclear how suitable it is for in-situ measurements in real-world work scenarios. To investigate this, we performed a series of studies designed to capture physiological and psychological data under differing (physical and mental) loading types with the intention of finding out how suitable such equipment is. Using reaction time (simple and choice) as a measure of performance we found similar correlations exist between loading duration and our measured indicators as those found in large-scale laboratory studies using state of the art equipment. Our results suggest that commercially available activity monitors are capable of collecting meaningful data in workplaces and are, therefore, worth investigating further for this purpose.

Introduction

Fatigue is, by nature, cumulative, and is influenced by many variables such as activity, time of day, sleep levels and social pressures. The impact of high fatigue levels, especially in high-risk workplaces, can lead to increased risk for employees, and is seen as a large contributor to workplace accident rates [START_REF] Rosa | Extended workshifts and excessive fatigue[END_REF][START_REF] Dobbie | Fatigue-related crashes: An analysis of fatigue-related crashes on Australian roads using an operational definition of fatigue[END_REF][START_REF] Haslam | Contributing factors in construction accidents[END_REF]. Risk assessment processes include attempts to assess the impact of workplace activities on fatigue levels. Typically these use qualitative self-reporting methodologies rather than quantitative data measurements. This type of data collection in workplace contexts is susceptible to response bias [START_REF] Morrel-Samuels | Getting the truth into workplace surveys[END_REF] and can result in a generalised view of risk. However the actual impact of activity upon fatigue is individualised. For example, tasks performed by a young person impacts fatigue levels to a lesser extent than tasks performed by an older person [START_REF] Avin | Age-related differences in muscle fatigue vary by contraction type: a meta-analysis[END_REF].

Many studies investigating the impact of activity upon performance have been undertaken. Most identify that an individual's performance is negatively impacted by activity, both physical and mental [START_REF] Pichot | Quantification of cumulated physical fatigue at the workplace[END_REF][START_REF] Galy | What is the relationship between mental workload factors and cognitive load types?[END_REF][START_REF] Mcduff | Remote measurement of cognitive stress via heart rate variability[END_REF][START_REF] Cinaz | Monitoring of mental workload levels[END_REF]. Each of these studies collected data using different methods, but the majority are conducted in a laboratory setting with large numbers of participants. In real-world work environments, individuals encounter naturally occurring stressors that may not be observed in laboratory experiments. Similarly the longer-term nature of fatiguing activities in the workplace and the limited number of participants who can be measured in in-situ studies may make it hard to reproduce known results.

The rise in popularity of wearable devices has provided additional tools for quantification of individualised activity levels. These devices are designed to operate autonomously and enable the real-time collection of quantifiable data in the field throughout the day. Physiological markers such as step and heart rates can be used to determine workload intensities, especially in physically-biased roles. Conversely, changes in the balance of the autonomic nervous system can be used to quantify cognitive loading. However, it is unclear how accurate these measures are when using commercial products designed primarily for the personal user. As a first investigation into this, we performed a series of single-person studies designed to see if we could reproduce known correlations between activity (both mental and physical) and response times. If we find similar correlations can be identified by these devices then it is worth further investigating their use in real-world work environments.

In this paper, we present the results of these initial studies investigating the use of low cost commercially available devices as a means of collecting data that has sufficient accuracy and granularity to identify physiological changes associated with mental and physical activity types which may indicate fatigue. We examine the suitability of such devices for use in the field, specifically for gathering data and monitoring of forestry workers throughout their working day.

Motivation

The forestry industry in New Zealand has a poor Health and Safety record with some 12,921 active Accident Compensation Corporation (ACC) claims between 2008 and 2013. More importantly the number of reported fatalities for the same period is 32. Such high levels of fatalities are concerning to the industry with reforms being planned to address safety of employees. Suggestions based on experimental data are limited, and difficult to source. Currently, the only practicable solution is seen as increasing the level of mechanisation resulting in removal of the employee from the worksite.

Recently (2014), the large numbers of incidents reported prompted the Independent Forestry Safety Review [START_REF] Adams | Independent forestry safety review[END_REF], designed to investigate factors that impact on health and safety within the forestry industry and to provide guidelines designed to minimize the number of incidents. It was identified that the forestry industry is one of the most dangerous occupations in New Zealand. Employees are 15 times more likely to suffer a workplace injury compared to other NZ based industries.

The physical nature of the work, long working days and tasks requiring high levels of concentration can all exacerbate the impact of fatigue [START_REF] Ellis | The effects of cold on the performance of serial choice reaction time and various discrete tasks[END_REF][START_REF] Pilcher | Effects of hot and cold temperature exposure on performance: a meta-analytic review[END_REF] with high demand tasks requiring more energy to complete. In workplaces with high task demands employees may experience the effects of fatigue earlier. There is also a recognition that the lack of welfare facilities in the forestry environment may be an additional contributor to fatigue.

Measurements

There are numerous physiological indicators that can be used to quantify activity. Step and heart rates have been successfully used to quantify physical activity [START_REF] Choi | Assessment of ambulatory activity in the republic of korea navy submarine crew[END_REF], whereas changes in the balance of the autonomic nervous system have been used as an indicator of cognitive activity [START_REF] Paritala | Effects of physical and mental tasks on heart rate variability[END_REF].

Currently seen as the gold standard for measurement of these variables are step counting for ambulatory activity and, electrocardiography for heart rate data collection. However, we must remember that in our proposed domain the devices we choose need to be minimally intrusive and capture data autonomously. Before we can assess suitable devices for the data collection we must first consider what the appropriate data to collect is. We discuss proposed identifiers of activity next, these will then inform subsequent choices of appropriate apparatus for data capture.

Step rate: The use of pedometers to measure an individual's daily activity has been used many times in differing domains. Designed to capture accelerations of the hip during gait cycles they count the number of steps taken by an individual over a given time period. Using the number of steps taken we can gain an insight into how role-based activity may contribute to excessive fatigue levels. This method has been used successfully to differentiate activity levels by role types in forestry harvesting operations [START_REF] Griffiths | Investigating Tools and Methods for Data Capture of Forestry Workers[END_REF] with large differences between manual and mechanised activity types being identified.

Heart Rate: Heart rate data captured throughout the course of a work period can be an used as an indicator of task demand. Higher heart rates typically accompany higher periods of physical activity as higher levels of oxygenated blood are required due to increased physiological demand. Increases in heart rate are individualized with demand being dependent on such criteria as age and fitness levels. However, maximal heart rate can be calculated from the general formula equation Maximal Heart Rate = 220 minus Age [START_REF] Karvonen | The effects of training on heart rate; a longitudinal study[END_REF]. The resultant figure can then be used in conjunction with resting heart rate to determine periods of high and low activity where activity is defined as deviation from the resting heart rate.

Heart rate variability (HRV): Heart rate variability is the time interval between successive heart beats. Shorter periods are indicative of active loading while longer time periods are indicative of rest. There are a large number of variables that can be extracted from collected data each providing an insight into autonomic nervous system activity. For our studies we use the low frequency/high frequency ratio of the power spectrum density of the heart. This variable has been found to correlate well with mental activity across differing levels of cognitive load [START_REF] Chandola | Work stress and coronary heart disease: what are the mechanisms?[END_REF][START_REF] Collet | Autonomic nervous system and subjective ratings of strain in air-traffic control[END_REF][START_REF] Patel | Applying neural network analysis on heart rate variability data to assess driver fatigue[END_REF].

Workload intensity: Workload intensity, or how hard an individual perceives their workload can be an indicator of increasing fatigue levels. Monotonous or repetitive tasks have been identified as a contributor to motivational levels [START_REF] Macdonald | The impact of job demands and workload on stress and fatigue[END_REF] with individual performance slowing as motivational levels decrease [START_REF] Wright | Effort processes in achieving performance outcomes: interrelations among and roles of core constructs[END_REF]. The Task Load Intensity Tool (TLX) developed at the Ames Research Center is designed as a self-reporting estimator of how difficult an individual perceives their workload. Using a six point scale it provides a workload score for workplace activities [START_REF] Hart | Development of nasa-tlx (task load index): Results of empirical and theoretical research[END_REF]. Increasing workload scores for tasks where the only change is duration can indicate increasing workplace fatigue [START_REF] Baulk | Does variation in workload affect fatigue in a regular 12-hour shift system?[END_REF].

Performance: Reaction time (both simple and choice) has been used many times to measure individual performance. It is a measure of the elapsed time between the presentation of a given stimulus and the participant's response. In simple reaction time the user responds to one stimulus whereas in choice reaction time the user must identify the correct response from a set of choices. Reaction time has been found to deteriorate with increasing fatigue [START_REF] Ellis | The effects of cold on the performance of serial choice reaction time and various discrete tasks[END_REF][START_REF] Brisswalter | Influence of physical exercise on simple reaction time: effect of physical fitness[END_REF][START_REF] Lim | Sleep deprivation and vigilant attention[END_REF] furthermore the time difference between choice and simple reaction time can give insights into the speed of mental processing.

State of the Art Methods and Tools

When considering our methodologies for collecting data we must also consider the accuracy of our proposed devices. The most accurate measure for step counting is manual counting. However, this is impractical for many purposes and in particular for our chosen domain -one cannot manually count steps in the workplace. The Yamax range of pedometers are widely regarded as the most accurate equipment for automatic step counting [START_REF] Tully | The validation of fitbit zip physical activity monitor as a measure of free-living physical activity[END_REF] and have been used in many studies investigating step rates [START_REF] Choi | Assessment of ambulatory activity in the republic of korea navy submarine crew[END_REF][START_REF] Castillo-Retamal | Measuring physical activity and sedentary behaviour at work: a review[END_REF][START_REF] Soroush | A 6 month physical activity intervention in university staff: effectiveness and health outcomes-The ASUKI Step Study[END_REF]. When comparing the accuracy of our chosen device (Fitbit Charge HR) many studies have found good agreement between actual and recorded steps taken [START_REF] Evenson | Systematic review of the validity and reliability of consumer-wearable activity trackers[END_REF][START_REF] Ferguson | The validity of consumer-level, activity monitors in healthy adults worn in free-living conditions: a cross-sectional study[END_REF].

Real-time data collection of cardiovascular activity in the workplace presents additional challenges. This type of data collection is typically done using an electrocardiograph and is undertaken at hospitals or dedicated research laboratories. The equipment can be bulky and cumbersome with an individual having wired sensors placed on the body. As previously discussed, our proposed domain is forestry operations in which traditional ECG measurement is not practical.

Wearable devices exist that are designed to capture data in free living activities. These devices range from chest strap based monitoring through to smart clothing containing electrodes to capture the electrical signals produced during a heart beat cycle. Devices are designed to be minimally intrusive to the individual and collect data autonomously facilitating use in the field.

The Polar range of products have been used extensively in studies investigating the cardiovascular system. For example, Paritala's work investigating the effects of physical and mental activity used the Polar RS800 monitor to capture the heart rate of 24 participants during laboratory testing [START_REF] Paritala | Effects of physical and mental tasks on heart rate variability[END_REF]. In a similar study the relationship between markers of work related fatigue and HRV of 28 participants used Polar devices for the data capture [START_REF] Völker | Relation between multiple markers of work-related fatigue[END_REF].

In the above section we have discussed the gold standards for data collection and identified limitations for use in workplace domains. Tools for performance and perceived workload intensity are numerous however, given our proposed domain our choice is limited. Any devices used to measure our required metrics will be worn throughout the working day by forestry workers and so should not cause discomfort during their physical activities. In order to collect data we therefore selected to use Fitbit Charge HR activity trackers to collect ambulatory data and the Polar RS8020CX fitness watch paired with a Polar chest strap to collect heart-rate data. In addition, field-based testing must be quick to conduct to minimise the impact on both productivity and the individual and as such we implemented an electronic version of the unweighted NASA TLX to collect data on perceived workload intensity as this will be quicker than a paper-based survey. For performance data we selected the Deary-Liewald Reaction Time application developed by the Centre for Cognitive Ageing and Cognitive Epidemiology [START_REF] Deary | A free, easy-to-use, computer-based simple and fourchoice reaction time programme: the deary-liewald reaction time task[END_REF]. It is an application specifically designed for conducting reaction time testing using portable computing devices.

Studies

The aim of these initial studies was to investigate whether the tracking devices and tools listed above could be used to replicate the results of large-scale, laboratory-based tests which investigate the effects of activity on fatigue. Performing monitoring studies of forestry workers is time-consuming and requires considerable buy-in from a number of different entities (forestry owners, contracting companies, health and safety organisations and the workers themselves). Before undertaking the field studies with workers, we therefore wanted to be certain that our equipment choices would be suitable and we could gather meaningful data. As such we focussed on evaluating combinations of different measurements across different activity types. Each of the studies described below were conducted with a single participant over short periods of time (the course of a day or a focussed activity) as a means to conduct such an evaluation.

Activity and Recovery

To assess the impact of activity on the physiological and psychological systems our first study was designed to assess the impact of differing loading types (physical and mental) on performance and psychological indicators. During physical loading the measurements were undertaken in an ad-hoc manner as and when opportunities presented themselves. Workload intensity was measured using an electronic implementation of the NASA TLX running on a dedicated server and measured at the same time as reaction time testing. Apparatus was worn for the duration of the monitoring exercise.

Physical loading

Monitoring sessions were undertaken over the course of a working day. The participant worked as a floor team member at a large retail outlet, a position requiring large amounts of ambulatory activity. Both ambulatory activity and heart rate data collection commenced at the start of the work day and concluded at the end of the work period. Workload intensity and performance measurement was undertaken at the start and end of the work period and at the participant's designated break times (2 x 15mins and 1 X 30mins).

When extracting data for heart rate variability, the raw data is put through an analysis program that computes the various indicators of cardiographic activity. For this task we used the gHRV software developed by Milegroup based at the University of Vigo in Spain. The application is specifically designed for the analysis of heart rate variability. 1As mentioned in 1.2, we use the ratio of low frequency to high frequency of the power spectrum density of the heart as an indicator of autonomic nervous system activity, inferring increasing fatigue from the increase of this ratio. The large datasets we create during monitoring can be used to provide point data, however, for our estimation of increasing fatigue we use the cumulative mean of the data over the duration of the monitoring period.

When assessing performance as the speed of mental processing (choice reaction time minus simple reaction time) we see an initial period of improvement followed by a period of slowing as the workday lengthens. The psychological impact was found to increase across duration with increasing perceived task intensity being reported. (Figure 1) Fig. 1: Speed of mental processing (left) and workload intensity (right) vs cumulative mean LF/HF ratio Activity during this period was measured as 22,322 steps (18.8km) with the majority occurring within the first 6 hours of the work session. The graphs indicate that speed of mental processing and perceived workload intensity are impacted by this high physical loading.

Cognitive loading

To investigate the impact of cognitive load we conducted experiments where driving was used as the mental activity and stressor. Driving is a task requiring constant vigilance and high levels of spatial awareness. The experimenter performed a 3 hour driving exercise on real roads encountering typical driving conditions. Reaction time testing in conjunction with workload intensity monitoring was undertaken at 30 minute intervals for the duration of the experiment. On completion of the driving exercise monitoring was continued to assess performance through a recovery period.

We found a similar increasing trend as that in physical loading however, the increase in LF/HF ratio was found to be higher.Workload intensity and performance were also negatively impacted over the duration of the experiment (Figure 2).

The higher number of data points collected during the driving experiments facilitates further analysis of existing relationships between our variables. We identified a good correlation for the majority of our measured variables. Table 1 presents the results of the correlation between our measured variables.

Discussion

When examining the results of our studies, we can see that each of our measured variables indicate an impact resulting from activity. In both physical and cognitive loading types, we see a reduction in performance across loading duration indicated by slowing of reaction times. We also observe that this reduction in performance occurs as the cumulative mean of low frequency/high frequency ratio increases (Figure 1). Furthermore, we note that cognitive load impacts the cumulative mean of low frequency/high frequency ratio to a greater extent than physical loading with higher values being recorded (Figure 2) for our driving study. These results are similar to the findings of other studies investigating the impact mental and physical loading on the autonomic nervous system [START_REF] Pichot | Quantification of cumulated physical fatigue at the workplace[END_REF][START_REF] Collet | Autonomic nervous system and subjective ratings of strain in air-traffic control[END_REF][START_REF] Mcduff | Remote measurement of cognitive stress via heart rate variability[END_REF].

In our driving study, we found a good correlation between our measured variables (Table 1) indicating relationships between performance and increasing levels of the high frequency/low frequency ratio. We also identified that performance continues to degrade on cessation of activity prior to improvement facilitated through a recovery period. These findings agree with those of previous studies investigating the impact of loading on the autonomic nervous system [START_REF] Collet | Autonomic nervous system and subjective ratings of strain in air-traffic control[END_REF][START_REF] Cinaz | Monitoring of mental workload levels[END_REF].

Similar to other studies [START_REF] Cinaz | Monitoring of mental workload levels[END_REF], we found perceived workload intensity increases as loading duration lengthens, individuals report higher workload scores later in the day for the same tasks. The perception of workload intensity was also found to relate to our measured physiological indicators. We identified higher workload scores were reported with increasing cumulative mean low frequency/high frequency ratios.

What we are seeking to identify here is the suitability of wearable devices for capturing meaningful data. As such the results described are not intended to prove relationships between activity, fatigue and response times per se. but rather act as a proof of concept that such methods and tools can replicate known correlations in such data. Given that they indicate this is possible, we can then move on to study their use in the field within our larger-scale studies with forestry workers.

Conclusions and Future Work

Our research question asked if low cost lightweight methods can be used for meaningful data collection of data pertaining to physiological indicators related to the impact of activity on performance. As found in other studies [START_REF] Takacs | Validation of the fitbit one activity monitor device during treadmill walking[END_REF][START_REF] Bowen | Investigating the use of activity trackers to observe high-risk work environments[END_REF] the Fitbit Charge HR successfully collected data on ambulatory activity. Having a similar footprint to a wrist watch we found the device minimally intrusive, and caused no discomfort to the individual.

The Polar chest strap used for the collection of heart rate variability proved to be capable of collecting meaningful data. However, the practicality of this device can be called into question. We found the fastening clasp on the chest strap can cause discomfort to the individual, resulting in reluctance to wear the device over longer periods. We also note a period of spiking may be present due to insufficient moisture between skin and electrode to accurately record heart rate data. This can be overcome by the application of electrode gel prior to the commencement of data capture.

As in other studies [START_REF] Rosa | Extended workshifts and excessive fatigue[END_REF][START_REF] Baulk | Does variation in workload affect fatigue in a regular 12-hour shift system?[END_REF][START_REF] Galy | What is the relationship between mental workload factors and cognitive load types?[END_REF], our results indicate workplace activity impacts both physiological and psychological states. We identify increasing values of the cumulative mean low frequency/high frequency ratio as loading duration extends. Furthermore, we identify that cognitive loading has a greater impact on the individual than physical loading. We have also identified that on cessation of activity performance continues to degrade prior to improvement. We acknowledge that monitoring undertaken during our study was brief and extended data collection over longer time frames is required to further identify any trends that maybe present. Furthermore, we acknowledge that the data collected represents a single individual as such future studies should incorporate a larger participant base to gain a better understanding of the physiological and psychological impact of workplace activity.

In conclusion, we assessed commercially available fitness monitoring devices as tools for physiological data capture under differing loading types. We found that the selected activity trackers are capable of collecting meaningful data providing researchers with additional tools for monitoring activity in free living. The use of the cumulative mean of the power spectrum density of the heart may be a useful indicator of the impact of activity on the autonomic nervous system and as such may be useful for the determination of workplace role/task intensity.

Fig. 2 :

 2 Fig. 2: Speed of mental processing (left) and workload intensity (right) v cumulative mean LF/HF ratio for driving experiment

Table 1 :

 1 Correlation of physiological and psychological variables

	Condition	Correlation R Comments
	Driving v Speed of Mental Processing	0.73	Speed of Mental Processing increases with loading duration
	Driving v Workload Intensity	0.98	Perceived workload increases with loading duration
	Driving v LF/HF Ratio	0.89	LF/HF Ratio increases with loading duration
	Recovery v Speed of Mental Processing	-0.69	Speed of Mental Processing decreases on loading cessation
	Recovery v LF/HF Ratio	-0.75	LF/HF Ratio decreases on cessation of loading
	LF/HF Ratio v Workload Intensity	0.92	LF/HF Ratio increases with increasing workload perception
	LF/HF Ratio v Speed of Mental Processing driving	0.72	Speed of Mental Processing increases with increasing LF/HF Ratio
	Speed of Mental Processing v Workload Intensity	0.56	Speed of Mental Processing increases with increasing perceived workload

available from https://milegroup.github.io/ghrv/doc.html


Mitali Sinha
email: mitalisinha93@gmail.com

Suman Deb
email: sumandebcs@gmail.com

An interactive elementary tutoring system for oral health education using an augmented approach

Keywords: Intelligent tutoring System, Wii Remote, Tangible interaction, 1

The conventional elementary education system in India is mostly guided by formal content development, focusing on areas like math, language, science and social-science. Children tend to retain very little knowledge about other important areas of learning like heath care, which needs to be developed in their foundation years. The education on oral health is one such example which is not given the focus they ought to be. Considering its importance in early education, we propose a learning environment where children would gain knowledge through constant interaction with an intelligent tutoring system. The system addresses the challenges in developing a learning environment for children by introducing audio-visual effects, 3D animations and customizing the tutoring process to provide user-controlled pace of learning. It also employs the Wii Remote for imparting a tangible hardware interaction with the interface. This paper describes the proposed system and the studies conducted on treatment and control groups to evaluate its efficacy and compare the learning outcome at various domains. Experimental results depict positive effects on learning in the proposed technology-enhanced environment and paves a way for the deployment of more interactive, technology-driven learning process in the elementary education system.

Introduction

Intelligent systems are rapidly becoming a part of the modern education environment which leads to what is known as technology enhanced learning (TEL). Although TEL is often related to e-learning, we can also refer to it as a hardware or ICT (Information and Communication Technology) based teaching environment. The teaching and learning process is highly benefited with the advent of technologies like computers. Turning computers into an intelligent tutoring system (ITS) and designing careful instructional strategies helps in building a learner-centric process. Our work presents the design and evaluation of an oral health based ITS for young children. The children must be educated at a very early stage and realize the importance of learning about oral health and hygiene. With a goal of designing a learner-centric process, an intelli-gent tutoring system is proposed which keeps track of a learner's progress and guide him or her by generating feedbacks throughout the process. Our idea is to introduce a gaming element in the tutoring system along with learning contents, as research indicates that children show a high degree of interest and engagement in a playful learning environment [START_REF] Montessori | The Montessori Method: Scientific Pedagogy as Applied to Child Education in "the Children's Houses[END_REF]. There is some evidence that favors the understanding of abstract concepts more easily with physical artifacts and tangible user interfaces [START_REF] Papert | Mindstorms: Children, computers, and powerful ideas[END_REF][START_REF] Resnick | logo, and design[END_REF]. The Nintendo Wii remote is introduced as a tangible tool to enhance the interaction with the system. The interface allows 3-dimensional interactions with the user delivering knowledge at both visual and auditory channel. By effective use of animations and audio-visual effects throughout the play, the system aims to successfully deliver educational contents to the learners. Our research work also compares the learning outcomes between the traditional learning environment and the technology-enhanced learning environment in the cognitive domain. We have also assessed the outcomes in the affective domain and investigated the development of psychomotor skills among the children.

Background and Related Work

An intelligent tutoring system possesses important features like personalization, interaction, and engagement in learning. In a traditional learning environment, the teaching and learning system often becomes a one-way process where the teacher acts as a controller of the pace of learning. In a large classroom environment, it becomes difficult for an instructor to keep track of the progress of each student individually. Research works suggested that learning outcome increases with the introduction of private tutors in the process [START_REF] Reiser | Dynamic Student Modelling in an Intelligent Tutor for LISP Programming[END_REF]. Private tutors are able to monitor the learning curve of individuals and suggest remedies whenever required. Thus, in the absence of private tutors, ITS can be used for tutoring different concepts. Unlike the traditional process, an ITS is designed carefully to deliver knowledge in a learner-controlled pace. It strives to understand the level of tutoring to be provided to the individual learners and delivers educational contents accordingly. There are also many examples where intelligent tutoring systems are employed and found to be effective [START_REF] Ritter | Cognitive Tutor: Applied research in mathematics education[END_REF][START_REF] Papadimitriou | Interactive problem solving support in the adaptive educational hypermedia system MATHEMA[END_REF][START_REF] Vanlehn | The Andes physics tutoring system: Five years of evaluations[END_REF][START_REF] Fossati | Supporting computer science curriculum: Exploring and learning linked lists with iList[END_REF][START_REF] Gertner | A coached problem solving environment for physics[END_REF].There is some evidence that shows an increasing interest and motivation in learning with the appropriate use of technology at early childhood stages [START_REF] Van Scoter | Technology in early childhood education: Finding the balance[END_REF][START_REF] Anderson | Television and very young children[END_REF]. The research works of Montessori also provided hints of young children grasping complex knowledge very easily in a playful environment with the help of physical artifacts [START_REF] Montessori | The Montessori Method: Scientific Pedagogy as Applied to Child Education in "the Children's Houses[END_REF]. Thus, in quest of providing an augmented tangible interaction to the users, the Nintendo Wii remote is employed in the system as a tangible tool.

The system also introduces a notion of game-based learning where children learn different skills and knowledge through a game. The significance and effects of digital games in educational domains are studied extensively. A multiuser learning game called Quest Atlantis resulted in learning gains for various topics and adopted in multiple school environment [START_REF] Barab | Making learning fun: Quest Atlantis, a game without guns[END_REF]. Also, a game-based approach to teaching nutritional course depicted good results on learning [START_REF] Jui-Mei | A gamebased learning approach to improving students' learning achievements in a nutrition course[END_REF]. As an experimental example, the oral health based tutoring system is proposed in our work which aims at imparting knowledge about dental hygiene. A limited number of research work has been carried out in the field of dental health education being addressed by an intelligent tutoring system. The study of Ho et al. [START_REF] Ho | Investigating the effects of educational Game with Wii Remote on outcomes of learning[END_REF] employs a Wii remote to investigate its effect as a TUI (Tangible User Interface). Their study showed improvement in memorability and fun factor in learning but does not provide better results in cognitive development among the users. Gerling et al. proposed a serious interface design for dental health based on the Wii remote interaction by introducing additional gaming elements [START_REF] Gerling | Serious interface design for dental health: Wiimote-based tangible interaction for school children[END_REF]. Another serious game was designed by Chang et al. which focused mostly on developing the psychomotor skills and did not keep an account of the interest and motivational factors which may result in dissatisfaction in the future [START_REF] Chang | Playful toothbrush: ubicomp technology for teaching tooth brushing to kindergarten children[END_REF]. Although, the above studies were successful in including gaming instincts, by carefully adapting user-centric designs and including better methodologies can definitely result in better learning outcomes. The proposed system attempts to provide a balanced learning system which includes both educational contents and fun factor. To make the learning interesting our system is developed in a 3-dimensional environment with the use of proper animations and visual effects. Finally, a detailed study of outcomes in cognitive, affective and psychomotor domain helps in strengthening the idea of employing an intelligent tutoring system in learning educational contents.

System Architecture

The system provides an enhanced learning environment to the users with the help of animations, hardware interactions and a tutoring process running in the backend. It aims for a proper blending of factual knowledge and its application. Animations and picture clips along with audio effects render the factual knowledge about dental health and hygiene. Users are asked to perform different tasks or solve a problem depending upon the factual knowledge gained at different levels (As an instance, the user is asked to match the name of a tooth to the 3D model of the tooth displayed on screen).

As the user works through the task, the system keeps track of his or her actions and help in progressing towards the solution through feedbacks.

The system is divided into different modules on the basis of their functionality as shown in Fig. 1. It comprises of a user interface through which the users interact with the system, a profile base that keeps the profile information and history of interactions for individual users, a hardware interaction module which facilitates the hardware interactions with the system, a knowledge evaluator that evaluates the knowledge of the user with the help of the task formation module and knowledge repository, a tutoring module which tutors the user throughout the task with necessary feedbacks with the aid of a feedback module.

User Interface and Gestural Interaction Module

The user interface facilitates interaction with the system. It is developed in a 3D designing environment using tools like Unity3D and Blender for experiencing an enhanced interaction and better understanding of the concepts. The system employs the Nintendo Wii remote for a tangible interaction. The Wii remote is a remote controller for a Japanese gaming console called Wii. Its motion sensing capability differentiate it from other traditional remotes. It has the ability to digitally manipulate items allowing gesture recognition and pointing of objects on a screen. The gesture recognition is guided by the three-axes accelerometer and its infrared sensing capability determines the location on the screen where the remote is pointing. The Wii remote connects with a computer via Bluetooth connection and thus provides a simple and wireless communication medium. It is employed as a tangible device in the system where it imitates the movement of a 3-dimensional brush model on the screen thus providing an augmented interaction with the system. The application includes a section where the user performs a gameplay with the Wii remote and learn few psychomotor skills.

Profile Base Module

The Profile base module is responsible for keeping the details of every user along with their performance history. The system is designed to impart knowledge to different groups of users with varying capacity and methods of learning and accepting information. This division is based on the Piaget's theory of cognitive development [START_REF] Piaget | Piaget's theory of cognitive development. Childhood cognitive development: The essential readings[END_REF] where he proposed four stages of cognitive development as shown in Fig. 2. According to Piaget, at the sensorimotor stage the children understands through senses and actions, at the preoperational stage they understand through language and mental images, at the concrete operational stage, they tend to gain knowledge through logical thinking and finally through hypothetical thinking and scientific reasoning at the formal operational stage. The proposed system focused on parts of the preoperational and concrete operational stages forming two levels namely POP (5-7 years) and COP (8-10 years). The user starts experiencing the system by first interacting with the user profile based module and entering their details (where the primary factor is the age group). The User_Name field helps the system to interact with the user with his/her name throughout the gameplay giving a sense of empowerment and making them incharge of their actions. The Age field is used by the system to direct the user to either POP or COP level where depending upon the level, information is provided to the users. Thus, data collected by the profile base module guide the tutoring system to continue the process of further evaluation.

Knowledge repository and task formation module

The knowledge repository is a metadata store that holds information regarding each concept, the problems generated and their solutions. Whenever a solution to a problem is submitted by the user, it is processed by the knowledge evaluator with the help of the knowledge repository. The task formation module is responsible for creating tasks for the user at different levels.

Feedback Module

The feedback module is responsible for guiding the users through stimulant learning and task solving. Three types of feedback mechanisms are designed as follows: audiovisual feedback serving as problem hints, movement-based feedback, and reportbased feedback.

Audio-visual feedback.

As the user initiates a task, the feedback module generates audio-visual feedbacks whenever the user finds difficulty in solving a problem. The feedbacks are generated in the form of text, video clips or animations on the screen.

To build up the interest of the user during the gameplay, they are also greeted for successful completion of the task. Fig. 3. Shows a snapshot of scenarios before and after the play. After successful completion of a level, the system appreciates the user's effort by displaying smileys and congratulating them. This kind of interactions helps in accelerating user engagement by addressing them emotionally and boosting their confidence.

Sensorimotor Movement based feedback. Feedback is also generated to help the user for making correct movements with the Wii remote. A pre-determined threshold value for the accelerometer data of the Wii remote is set. If the accelerometer data acquired at any instant during the play crosses the threshold value, a feedback is generated. For example, if the user is moving the Wii remote too fast crossing the limit, then the user is prompt on screen to slow down the pace. Again if the user is showing no movement for a preset amount of time, he or she is asked to either quit or continue the play.as a result, the movement based feedback helps in developing psychomotor skills by limiting the movement of the Wii remote.

Report based feedback. At the completion of each level, a performance report is presented to the user giving a brief description of the outcome of the play. This report generation at the end of each level provides a basis for determining the level of difficulty to be adapted in next stage of the play and also helps in monitoring the psychomotor development in children.

Tutoring System

The users are tutored throughout the process by the tutoring system with the help of the information gathered from the profile base module, knowledge evaluator, and feedback modules. The tutoring system is guided by some predefined rules depending on which it determines the level of knowledge provided to the particular user. It then interacts with the user through the feedback module. On the basis of the information from the knowledge evaluator, the tutoring system decides the level of factual knowledge delivered. It processes knowledge at two levels (POP or COP) depending on the pretest results. Fig. 4 gives the illustration of a generic scenario of problemsolving by the tutor system. As a problem is given to the user, the tutoring system helps him or her through the process by providing hints or explanations regarding the problem. The users are tutored with textual, video or animations by the feedback module. A problem is then presented to the user based on the concept discussed to decide whether to further tutor the user or move on and take next actions.

The application development

The application is developed with a goal of blending learning content and gameplay effectively. In quest of finding ways to provide a tangible learning experience, the Nintendo Wii remote was selected. Therefore, the user gets a multi-model interactive environment where the sense of sight and hearing is exploited by the user interface and the sense of touch is provided by the Wii remote.

The interface design

The interface design constraints are guided by the principles of Mayer's cognitive theory of multimedia learning [START_REF] Mayer | Multimedia learning[END_REF]. Mayer proposed five principles for effective multimedia design for the better understanding of educational contents as follows:

 Off-loading. Moving some essential information from visual channel to the auditory channel would help in the better transfer of knowledge.  Segmenting and pre-training. Better outcomes are observed when lessons are presented in learner-controlled segments allowing time between successive segments. Also providing pre-training like knowing the names and behaviors of the system would facilitate the learning process.  Weeding and Signaling. Excluding extraneous materials and including signals results in better understanding of a specific concept.  Aligning and eliminating redundancy. Aligning refers to placing the graphics and related information at close proximity for better correlation. Also, avoid presenting redundant information visually and in spoken words.  Synchronizing and individualizing. Transfer of knowledge is facilitated if narration and corresponding animation are presented simultaneously. Also, it is important to make sure that the learners possess skill at holding mental representations.

The first and third principles of Mayer's cognitive theory of multimedia learning is followed by using both audio and visual contents representing only the important materials. The system is designed to represent knowledge at different levels depending upon the ability of the user to grasp the concepts. Thus the second principle is justified by allowing a user-controlled pace of learning. The design is thoroughly revised for any redundant information being delivered and also placing graphics and related information in close proximity thus adhering to the fourth principle. Finally, Mayer's fifth principle is followed by narrating information and playing related animations simultaneously. The interface is designed using 3-dimensional designing tools to provide a better user experience since they primarily interact with the system through the interface. The Blender 3D modeling tool is used to create the teeth models and other objects for the game world. The models are then imported into the unity game engine as shown in Fig 6, where the scripting is carried out in C# language.

The game concept

The game supports two stages of learning as mentioned earlier i.e. the POP and COP stage. The POP stage is designed for the children belonging to the age group of 5-7 years while the COP stage is for the age group of 8-10 years. Although the underlying idea of the game is same for both the stages, the knowledge representation is slightly different. In the POP stage, the factual knowledge is represented to the user mostly through storytelling, animations, and auditory means. While in the COP stage, concepts are represented more broadly using textual, audio and video contents. The preknowledge test helps the system decide to either provide the user with the POP or COP stage. This is important because if the user starts with the COP stage and he or she is unaware of the basic concepts and terminologies explained in the POP stage, it may result in a gap in the learning process. Again if the user is given with the POP stage and finds the facts repetitive, he or she may lose interest in learning.

The idea of the game is to first provide factual knowledge to the users and then evaluate them by proposing simple tasks. As an instance, in the POP stage at first, the user is tutored and introduced to the shapes and names of the teeth by animating each tooth model on the screen along with audio effects. After each such sessions, the users are asked to answer some questions or solve a problem related to the concepts explained which are then evaluated by the knowledge evaluator. If the submitted answer is incorrect, the system provides some hints dynamically or suggests the user revise the concepts by going back to the animations as depicted in the Fig. 3.

The interface also includes three buttons which help to switch between three sections namely "Facts", "Stories", and "Play". The "Stories" section includes small concepts related to dental health in the form of stories since storytelling tends to have a positive impact on learning among small children [START_REF] Ryokai | CHI'99 extended abstracts on Human factors in computing systems[END_REF]. The "Play" section helps in developing psychomotor skills of children by helping them to learn proper brushing techniques.

The Nintendo Wii remote is employed in the environment as a tangible tool to imitate the brush model on screen. The user needs to hold the Wii remote and gently clean away the black dots making small circular movements as shown in the Fig. 3. The gameplay is designed using an adaptive algorithm with different levels. If the user is not able to solve the assigned task at the first level, then the subsequent level is made easy by altering some game elements (like a number of black dots or time limits) to maintain his or her level of satisfaction. Similarly, if the user completes the task very quickly then the next level is made more difficult to hold his or her interest in play. The system also provides tips and hints to the user throughout the play and feedbacks are dynamically generated by the system whenever required. A report based feedback helps to increase the level of interest as they can assess their own improvement at the end of each session. To adhere to the gaming standards, our gameplay introduces certain gaming aspects as follows:

 Challenges. Various challenges are included in the play to uphold the interest of the users. A timer is set at the start of each level and the user needs to complete the task within the time constraint. Also, the accelerometer data acquired from the Wii remote is used to restrict the user movement and generating warning when it accesses the predefined threshold value.  Animations. The game effectively makes use of animations which scales down the cognitive load and thus facilitates learning.  Personalizing information. A login system is employed in the system which helps in personalizing user information to boost their interest and consciousness towards the play.

 Fantasy context. Involvement of technologies like the computer and the Wii remote in the education process add a fantasy context to increase engagement and motivation of the users.

Our system thus successfully maps to the Bloom's Taxonomy of Learning Domain [START_REF] Bloom | Bloom taxonomy of educational objectives[END_REF]:

 Affective Domain. The system manages to uphold the motivation and satisfaction level of the users by personalizing the game, introducing different in-game challenges and various feedbacks.  Cognitive Domain. The "Facts" and "Stories" section impart the factual knowledge in form of textual, animations and audio-visual effects.  Psychomotor Domain. The "Play" section helps in developing the motor skills to facilitate the proper brushing techniques of the users.

Research Methodology

Our research work primarily focuses on investigating the outcomes of learning in the cognitive and affective domain. It also includes an assessment process tracking the psychomotor development of the children throughout the play. Our study tries to address one overarching question and three sub-questions as follows:

Overarching research question. Does the proposed technology enhanced learning environment helps in improving children's outcome of learning?

Sub-research question 1. Does the system accelerate cognitive learning in children?

Sub-research question 2. Does the system arouse learning interest and improves learning outcome at affective domain?

Sub-research question 3. Does the system help in developing psychomotor skills at the end of the learning process?

Study Design

An experimental study design was adopted using a pre-test and post-test interventions.

Our focused group for user study was grade-3 and grade-4 students of a primary school in Tripura, India. The experimental design comprised of 80 students (grade-2 and grade-3 students) divided into two groups i.e. the treatment group and the control group (40 students each). The treatment group went through the experimental setup and completed their tasks as instructed (each participant were asked to play or interact with the system using the Wii remote). On the contrary, the control group was provided with a traditional classroom environment, where an instructor was teaching a group of students. In the case of the control group, the instructor did not use any technologyaided tools for teaching and they learned new concepts by listening to the instructor.

Thus, both the groups are delivered same knowledge base about dental hygiene but experienced different environments of learning.

To ensure that the members of the two groups (treatment and control groups) are equivalent prior to the treatment, a matched random assignment technique was considered. This technique is adopted to normalize the assignments of participants to different groups based on characteristics like age and their familiarity with playing video games (which was recorded by interviewing the participants and their A sample of the matched random sampling is shown in Table 1.

Instruments

Our user study comprised of different instruments used to assess the learning outcomes at various domains.

Cognitive domain. The pre-tests and post-tests interventions served as an instrument to investigate the outcomes at the cognitive domain for both the treatment and control groups. Before conducting the experiment, a pre-test was carried out on the topic of dental hygiene and the scores of each participant (treatment and control groups) were recorded. At the end of the experiment, a post-test was conducted depending upon the knowledge being delivered through the process. Some of the questions are listed as follows:

 Name the different types of teeth?  What is the function of a molar and canine teeth?  What is the cause of cavities?  What is the name of the tooth model? (An animation of a tooth model is displayed on screen)

The pre-test and post-test results were analyzed to find whether there was a significant difference between the learning curve of the treatment and the control groups. An analysis of the variance was carried out by One-Way ANOVA using the SPSS statistical tool.

Affective Domain. The affective domain plays a transparent role in education. Emotional needs act as an unseen bridge between the physiological needs and selfrealization or success. Therefore, it is equally important to take care of the affective domain in learning along with other factors like cognitive and psychomotor skills in children. To assess the affective domain in our study, we used an anecdotal report for each individual, a checklist and finally survey questionnaires.

Anecdotal report. The first instrument for assessing the affective domain was an anecdotal report which provided a brief narrative account of the participant's actions in intervals throughout the session. One of the observers present in the experimental area recorded a detailed description of each participant's activity carefully. The process was carried out for both treatment and control groups at three intervals each with a duration of 120 sec. To provide a strong support to the anecdotal report created by the observers, we also recorded the experiments and captured users' reactions which were used later to interpret their behavior. During the observation, information was collected regarding how children communicated verbally or nonverbally. Physical gestures and movements, reactions towards the teacher or the game-based learning environment, and interactions with peers were also summarized. Fig. 7 shows an example anecdotal record (record presented here shows a part of the collected data). Only observable actions were recorded in the anecdotal report and no generalization of the attitude and causes were written.

ANECDOTAL REPORT

Participant's Name: Meenakshi Das Played Video games: Yes Date: 1/11/XX Age: 8 years Group: Treatment Observer: Mitali Sinha Interval I: Meenakshi came into the classroom and took a seat. She wished the instructor "Good Morning". As the instructor gave instruction she looked at him. She raised a hand to ask a query as the instructor was explaining. She asked if she will be rewarded for her victory in the game.

Interval II: She sat in front of the computer and took the device in her hand. She started reading the instruction on screen and proceed as suggested by the instructor.

Interval III: At the middle of the activity, at times she exclaimed Wow!. She also informed the instructor "Sir, I want to know more about our teeth and how they catch cavities.

Fig. 7. A sample anecdotal report

Checklists. Checklists were used as our second instrument for information gathering. In this method, a number of specific traits or behavior was pre-defined by the researchers that are relevant to their work or motive of research. We designed our codes by studying various existing literature based on classroom observations [START_REF] Roehrig | Development and use of a tool for evaluating teacher effectiveness in grades K-12[END_REF][START_REF] Sawada | Measuring reform practices in science and mathematics classrooms: The reformed teaching observation protocol[END_REF]. One of our observers sat with the checklist and recorded the actions of both the treatment and control groups. Each participant of both groups was observed at three intervals (120 s for each interval) and their behaviors were recorded positive or negative depending on their gestures and reactions. Table 2 shows the sample checklist of both treatment and control group at an instant. Survey Questionnaire. The third instrument used in our study was the surveyquestionnaire. Keeping in mind the young age of the participants the survey was conducted orally. The observers asked relevant questions to the participants in order to draw effective conclusions regarding their engagement and interest throughout the activity. The young participants were asked to describe the activity in their own words. Some of the survey questionnaires are as follows:

 How do you feel in learning by playing games?  Did you enjoy studying?  Would you like to learn and play again?

The accumulated reactions and comments were grouped as positive, negative and neutral. Comments including adjectives like "Awesome", "Wow", "Good", "Superb", "Fun", and "Cool" were grouped as positive comments. While statements including words like "not fun", "boring" etc. were grouped into negative comments. The neutral group comprised of statements that were irrelevant to the topic, providing neither positive nor negative views. Such group contained statements including words like "Okay", "interesting but too easy", "not my type" etc. The treatment and control group were compared against these three partitions of reaction (positive, negative and neutral) to investigate which group (treatment or control) had more positive comments. The group that showed higher positive comments were concluded as providing more engagement to the participants and thus better performance.

Psychomotor Domain. To investigate the effect of the proposed system in the psychomotor development of the children, the mean error (in performing correct gesture i.e. correct brushing technique) of each participant of the treatment groups were observed. The system keeps track of the psychomotor development of each individual and produces a report. This report is analyzed to assess whether the children developed the skills after going through the experiment.

Results and Discussions

Cognitive Domain

A pretest was carried out at the beginning to evaluate the internal validity of the experiment conducted, where both the groups were evaluated on their pre-knowledge about dental health and care. The test was based on the educational content to be delivered throughout the experimental process. The pretest questions consist of some basic to advanced questions regarding oral health. At the end of the experiment, a posttest was conducted to assess the learning outcomes of the participants. A One-Way Analysis of Variance (ANOVA) was formulated using the SPSS tool to evaluate the null hypothesis that there is no difference in the learning outcomes among children in the traditional learning environment and the proposed learning system (N = 80). Table 3 shows the mean of the difference between pretest and posttest results of participants in the treatment group (M= 3.33, SD=3.724) and control group (M=1.68, SD=3.362). The mean value of 3.33 of treatment group depicts that the difference between the pretest and posttest results in the treatment group is more significant than the difference in the control group with the mean value of 1.68. The assumption of homogeneity of variances was tested and found tenable using Levene's Test, F (1, 78) = 0.05, p = 0.943. The results of ANOVA was significant as shown in Table 4 with F (1, 78) = 4.327, p = 0.039. Thus, there is a sufficient evidence to reject the null hypothesis and conclude that there exists a significant difference in the learning outcomes of the children in the treatment and control group.

Affective Domain

Analysis of Anecdotal Records. To determine affective learning among the participants of the treatment and control group, we first performed a detailed analysis of the anecdotal records prepared by the observer. A report was produced for each participant in both treatment and control groups noting down their behaviors at three intervals. The sample individual report is shown in Table . 5. Since the anecdotal report provides a detailed study of each individual, we broke down the observed behaviors into few set of behaviors (which was not pre-defined) for the sake of comparison.

Mean score was calculated out of the three intervals for each individual participant.

Again the mean scores of each participant in treatment and control group against enlisted behaviors were tallied and a final score for the two groups was presented. The final table of comparison between treatment and control group for the anecdotal report is described in Table 6. Analysis of Checklist report. Our second instrument that is Checklists provides a means of quickly recording the presence or absence of a behavior amongst the participants. Unlike the anecdotal report, the checklist comprises of pre-defined rubrics on which we performed the comparisons. The checklist for the first interval for both treatment and control group is shown in Table . 2. After three intervals the observations were compared and the final results were obtained by calculating the mean scores of treatment and control group towards the enlisted behaviors. This is shown in Table . 7. Analysis of Survey Questionnaire. Further ambiguity check of the intended results was carried out by conducting a post-activity survey. In the post-activity survey, each participant of treatment and control groups were asked about their experience during the experiment. The answers of each participant were recorded and grouped into three categories i.e. positive, negative and neutral. Fig. 8. Shows the distribution of the comments for both the treatment and control groups. The graph depicts that the treatment group showed more positive response than the control group. Also, the control group produced a more negative reaction in comparison to the treatment group. A few participants' reaction in both the groups were neutral and showed the least interest in both cases. However, we found a major number of participants interested in learning in the treatment group and thus get some evidence of better performance in the treatment scenario.

Psychomotor Domain

The report generated by the system at each level corresponding to each individual is analyzed to check the improvement in psychomotor skills among the children. The system recognizes the number of attempts of each participant during the experiment and the mean error is calculated from the results. The Fig. 9 shows the comparisons between the mean error values at the first and last levels. As depicted by the graph, the mean error of many participants decreased eventually from the first level to the last level. This fact gives an evidence that the participants were making less error in the movement of the Wii remote and were successful in completing the levels in the game. Thus, we conclude that the participants showed improvement in developing the skills generating less mean error at the last level in comparison to the first level of the game play.

Results of Survey Questionnaire

Treatment Group Control Group

Conclusion

In this paper, we presented an enhanced learning environment which is guided by an intelligent tutoring system and investigated its effect on the learning outcomes of the children. Our work tries to address the areas of learning which is important but not very widely included in the education system's curriculum at present. We try to introduce an environment of the education system where we can enhance the outcomes of learning by increasing the interest and motivation of children towards learning new concepts. The proposed system was able to successfully deliver educational contents to the children and help in their cognitive development. By introducing the notion of the game and 3-dimensional contents in the application, the system was able to gain the attention of the participants thus improving the affective domain. Also at the end of the experiment, the participants were able to improve psychomotor skills by the technology-enhanced environment. Thus, the use of technology and enhanced interactions depicted better learning outcomes arousing the interests of young children in learning.

We now discuss a few limitations and future directions to our research work. The proposed system was developed to address primarily the dental health based contents.

To generalize the educational contents proper care must be taken considering the target users else it would not be able to produce the desired results. Although our study depicted positive effects on learning, large-scale testing of the system with varying target groups is to be done in the future.

Fig. 1 .

 1 Fig. 1. System Interconnection Modules

Fig. 2 .

 2 Fig. 2. Piaget's Stages of Cognitive development

Fig. 3 .

 3 Fig. 3. Scenario before and after the successful completion of task (left to right)

Fig. 4 .

 4 Fig. 4. Automatic feedback generation process by tutor module Fig.5. represent a more specific scenario in case a user fails to give a valid answer. A problem is displayed on the screen and the user is asked to choose the correct answer. Since the user failed to give the correct answer, the tutoring system displays a hint on screen. A molar tooth model is displayed along with an audio instruction playing in the background.

Fig. 5 .

 5 Fig. 5. Problem displayed on screen; Hint generated by tutoring system

Fig. 6 .

 6 Fig. 6. Teeth model in Blender; Teeth and Brush model imported in Unity 3D game engine.

Fig. 8 .

 8 Fig. 8. Survey Questionnaires results

Fig. 9 .

 9 Fig. 9. Comparison between mean error values of the participants at end of the treatment

Table 1 .

 1 Matched Random Assignment

	Participant ID	Age	Played Video games	Group
	01	8	yes	Treatment
	02	9	yes	Control
	03	8	no	Treatment
	04	8	no	Control
	05	9	yes	Control
	.	.	.	.
	.	.	.	.
	.	.	.	.
	.	.	.	.
	80	9	no	Treatment

Table 2 .

 2 Sample checklist for recording behaviors of treatment and control group (Interval I).

	Behaviors	Treatment Group 1 2 3 4 5	40	1	Control Group 2 3 4	40
	Looking at Instructor/ Screen
	Asking queries to Instructors
	Looking outside classroom
	Feeling Sleepy
	Talking with others (on irrelevant topic)
	Doing other works
	Sharing thoughts with peers after activity

Table 3 .

 3 Mean Score table

	Group	Mean	Std. Deviation	N
	Control	1.68	3.362	40
	Treatment	3.33	3.724	40
	Total	2.50	3.621	80

Table 4 .

 4 One-way ANOVA test results.

		Sum of Squares	df	Mean square	F	Sig
	Between groups	54.45	1	54.450	4.327	0.039
	Within groups	981.55	78	12.584
	Total	1536.00	80
	Corrected Total	1036.00

Table 5 .

 5 Sample Individual report at three intervals and their mean scores.

			Intervals		Mean
	Behavior	I	II	III	(%)
	Not paying attention to activity				33.33
	Trying to understand the instructions				66.67
	Actively participating during the procedure				66.67
	Feeling bored				33.33
	Interested in other topics not related to current				66.67
	Concentrating on others' works				33.33

Table 6 .

 6 Comparison between Treatment and Control group for Anecdotal Report

		Treatment	Control
	Behavior	Mean	SD	Mean	SD
	Not paying attention in activity	26.66	0.01	66.66	0.01
	Trying to understand the instructions	73.33	0.02	30.00	0.03
	Actively participating during the procedure	66.66	3.02	36.66	0.02
	Feeling bored	29.99	0.03	36.66	0.02
	Interested in other topics not related to current	50.00	3.33	46.66	0.02
	Concentrating to others' works	29.99	0.03	30.00	0.03

Table 7 .

 7 Comparison between Treatment and Control group for Checklist Report

	Behavior	Treatment	Control
		Mean	SD	Mean	SD
	Looking at Instructor/ Screen	71.26	0.02	35.01	0.03
	Asking queries to Instructors	69.67	2.03	35.21	0.02
	Looking outside classroom	21.23	0.02	50.53	0.03
	Feeling Sleepy	32.26	0.02	36.20	0.01
	Talking with others (on irrelevant topic)	25.00	2.27	39.89	0.01
	Doing other works	28.78	0.03	27.63	0.03
	Sharing thoughts with peers after activity	68.82	0.03	25.43	0.02