Mobile intelligent tutoring systems have the possible to present low-priced, one-to-one aid to scholars outside of the traditional schoolroom and computing machine lab scenes. The focal point of this paper is to sketch the usage of Mobile Intelligent Tutoring Systems in back uping the Mathematics human coachs in secondary schools and the function that nomadic devices can play in circulating and back uping the cognition gained by intelligent coachs. The paper reviews desktop Intelligent Tutoring Systems and how the same can be used in nomadic devices. The concluding portion of the paper examines the challenges faced in the development of Mobile Intelligent Tutoring Systems.
The general public presentation in mathematics among secondary school pupils in Kenya has non been impressive for many old ages ( KNEC, 2000 ) . Much has been done and said with purposes of bettering public presentation with small success including debut of “ Strengthening of Mathematics and Science in Secondary Education ( SMASSE ) Undertaking ” , launched in Kenya in 1998 and funded by Japan authorities. It is aimed at the betterment of mathematics and scientific discipline instruction through In-service Training ( INSET ) for instructors ( Nancy, Alice, 2007 ) . Poor public presentation is attributed to several factors among them attitude of pupils and instructors, deficiency of learning installations such as books and unequal remedial or follow-up tutoring in most schools. Whereas there is demand to assist scholars develop a deeper conceptual apprehension through such techniques as tutoring when they are larning a new sphere ( Lane, 2006 ) , that is desiring.
Mathematicss is a hard capable both to learn and larn. Mathematicss is besides a topic, which requires difficult work, and batch of pattern – the paramount facets for larning mathematics. Learning mathematics comprises foremost having facts, rules, and so larning how to use them ( Garry, 1996 ) . Teachers may desire to pass more clip with pupils but human resource is normally the chief restraint due to high student-to-teacher ratio witnessed in schools.
The broad usage of cell phones in society has led research workers to look into methods to use nomadic devices in instruction ( Castells, 1999 ) . Presently, there are around 16 million cell phone endorsers in Kenya with the figure projected to travel up following licensing of 4th Mobile operator – YU ( Communication Commission of Kenya ) .
Harmonizing to Brown ( 2003 ) and Kam etal ( 2009 ) , the nomadic device has been argued to be an appropriate tool for educational bringing in the development states. The statement behind this is that nomadic device is low-power device that can be used in topographic points without electricity. Although nomadic device such as cell phone is mostly purchased for voice communications – which users rely on for their societal and economic demands – it is besides able to run educational package that support visuals and voiceovers ( as cited in Kumar, 2009 ) . Most of all, the cell phone is the fastest turning engineering platform in the development states. There are 2.2 billion nomadic phones in developing parts like Africa and India, as compared to merely 11 million desktops ( CNN, 2009 ) .
Teaching pupils on a one-to-one footing significantly influences the grade of cognition and accomplishment retained by the pupil. Bloom ( 1984 ) suggests that one-to-one tutoring is the most effectual scheme known, by and large giving two standard divergences better public presentation than traditional direction.
For the intent of this paper, the term “ nomadic device ” comprise of criterion cell phones, smart phones ( those using an operating system supplying voice services every bit good as extra informations processing applications ) , and personal digital helpers ( PDAs ) – supplying informations treating without voice capablenesss. Whereas laptop computing machines are portable, users interact with them in ways that are more similar to desktop computing machines than they do with smaller devices e.g. usage of keyboard. Therefore, it does non fall under ‘mobile device ‘ class.
Table 1.1 Comparisons of Desktop and Mobile Tutoring Systems
Full size keyboard
14+ inch show
2-5 inch show
Classrooms and computing machine labs
Anywhere and anytime
2. Intelligent Tutoring System
Hafner ( 2000 ) defined Intelligent Tutoring System ( ITS ) as “ educational package incorporating an unreal intelligence constituent. The package tracks pupil ‘s work, orienting feedback and intimations along the manner. By roll uping information on a peculiar pupil ‘s public presentation, the package can do illations about strengths and failings, and can propose extra work. ” ITSs have been used to help pupils with prep, trial pickings, and appraisal ( ISTE, 2007 ) .
An ITS can be used to enable the pupils work independently, to better their apprehension of constructs within related sphere, and to take advancement of job work outing ability for each of them ( Martin, 2001 ) . On the other manus, an ITS can be able to help non merely the pupils but besides the instructors in developing and managing classs ( Shin, Norris and Soloway, 2006 ) . Harmonizing to Korhan ( 2006 ) , “ Intelligence involves mental capablenesss such as the logical thinking ability, planning, work outing jobs, believing abstractly, groking thoughts, and larning ” . Furthermore, it is related to creativeness and personality of the individual harmonizing to psychological science. Conversely, mathematics is as a incubus for many pupils. This may take to pupils doubting their creativeness, endowment, and motive when analyzing mathematics. In this sense, the tutoring systems must hold the capableness of existent instructors, and it must move like human coach in a category. Information technologies can raise up the effectivity of learning mathematics in a category ( Kinshuk, 2002 ) and hence regarded as one of the topics in Artificial Intelligence ( AI )
3. Background of ITS
Computers have been used in instruction since 1960s ( Martin, 2001 ) . Intelligent Tutoring Systems are computing machine systems designed for support and betterment of acquisition and learning procedure in the sphere cognition.
Even though Intelligent Tutoring Systems began with Computer-Aided Instruction ( CAI ) , they differ from them in some ways. First, the interfaces, in CAIs, are of all time inactive for each pupil and the information presented to each pupil is precisely the same for all the clip ( as cited in Mitrovic et al. , 2007 )
Harmonizing to Koedinger et Al. ( 1995 ) , ITSs use the cognition for pedagogical procedure so that the system tries to find what the pupil knows or does non cognize. Contrary to ITSs, CAIs have premises about what the pupil knows. Therefore, the same course of study is presented to pupils in CAIs, even though the predating cognition is necessity for a pupil.
The other difference between them, harmonizing to Koedinger et Al. ( 1995 ) , is with the feedback system. Some CAIs have the capableness of inquiring inquiries to pupils. However the feedback system of them is limited to indicant of whether the pupil reply was right or incorrect, merely. ITSs, on the other manus, attempt to find the pupils ‘ failings on a subject utilizing the sphere and pupil theoretical account as shall be depicted in subdivision 4 below.
Most Computer-Based Instructional ( CBI ) applications and systems, including ITS, still shack chiefly on the desktop. Harmonizing to Eamon ( 2004 ) , ITS have been shown to be extremely successful in bettering pupil acquisition in the schoolroom. When ITS is integrated into school course of study, pupils use the coachs during school hours in computing machine labs and schoolrooms.
The enlargement of the desktop ITS to the nomadic learning universe of Mobile will, doubtless, supply great benefit for pupils and instructors likewise. A nomadic intelligent coach has the possible to present the important advantages of intelligent tutoring systems to a broad audience of scholars and spread out coach usage to exterior of computing machine labs and schoolrooms therefore supplying robust and flexible acquisition chances to pupils “ anyplace ” and “ anytime ” ( Farooq etal, 2002 ) . It will besides be of aid for pupils on the move such as nomads who may non acquire adequate human tutoring in category besides heightening student-centred acquisition.
4. How Intelligent Tutoring Systems Work
ITS for mathematical jobs was planned and designed to ease pupils in acquisition and name on pupil ‘s mistakes and efficaciously generate accounts for those mistakes ( Burns, Capps, 1988 ) and offer a pupil monitoring system that includes learning advancement and relevant statistical informations.
The end of ITS is to supply the benefits of one-on one direction automatically and be efficaciously.
Like any other preparation simulations, ITS enables participants to pattern their accomplishments by transporting out undertakings within extremely synergistic acquisition environments.
However, ITS goes beyond developing simulations by replying user inquiries and supplying individualised aid. Unlike other computer-based preparation engineerings, ITS systems gauge each scholar ‘s actions within these synergistic environments and develop a theoretical account of their cognition, accomplishments, and expertness. Based on the scholar theoretical account, ITSs tailor instructional schemes, in footings of both the content and manner, and supply accounts, intimations, illustrations, presentations, and pattern jobs as needed ( James and Sowmya, 2007 )
Intelligent Tutoring System
Figure 4.1 Intelligent Tutoring System Model
Intelligent tutoring systems have their foundation in the unreal intelligence, more specifically adept systems, and computing machine assisted direction subjects. Burns et Al. ( 1988 ) depict the “ intelligence ” of this package as the aggregation of the five subsystems shown in Figure 4.1 above.
The first is an adept theoretical account stand foring the sphere cognition or capable affair expertness. This cognition comprises the apprehension of the capable affair that an expert has in the tutored country i.e. adept theoretical account merely represents the expert cognition and the ability to work out jobs within a sphere.
The 2nd theoretical account is the pupil ‘s. This theoretical account represents the cognition, accomplishments, behavior and other properties of a pupil larning the sphere. This theoretical account let the ITS know who it ‘s learning ( James et al. , 2007 ) and tries to find pupil ‘s mental provinces. This faculty generates the pupil theoretical account with all information about the single scholar. It provides the information such that what the pupil knows or does non cognize, any misconceptions, grade of forgetfulness, concluding accomplishments etc. ( Korhan, 2006 )
The 3rd is the direction theoretical account, which is responsible for acknowledging pupil input and reacting to student actions i.e. enables the ITS to cognize how to learn, by encoding instructional schemes used by the tutoring system. The teacher theoretical account selects the most appropriate instructional intercession based on the cognition of a pupil ‘s accomplishments, strengths and failings, participant expertness degrees, and pupil acquisition manners. Additionally, the teacher theoretical account may besides take subjects, simulations, and examples that address the pupil ‘s competency spreads. It is besides known as pedagogical or coach faculty ( Martin, 2001 )
The 4th is the instructional environment or sphere that provides support to the scholar. It consists of the activity and tools, and to some widen the state of affairs, provided by the system to ease acquisition.
The last constituent is the interface, an indispensable constituent that provides the agencies by which the user can pass on with the system. It is the integrating of the theoretical accounts that separate ITS engineering from other signifiers of computer-aided direction ( Heffernan, Koedinger and Aleven, 2003 ) .
Harmonizing to Trojahn et Al. ( 2002 ) , ITS have the informative attack in which direction is understood to be the transmittal of cognition necessitating the teacher/instructor to supervise the pupil invariably, particularly in the job work outing procedures. It takes into history the capacity for acquisition and the cognition of the pupil in that topic.
ITS ‘s are adapted to each pupil by agencies of their diagnostic accomplishments which examine the pupil ‘s cognition and the structuring and presentation of cognition. They besides make usage of a assortment of techniques to keep the user ‘s attending ( equated to human coach motive ) and ease the transmittal of the coveted cognition. Intelligent developing systems besides portion this attack, although in these instances the procedures are aimed more towards specific job resolution activities. The coach guides the direction procedure harmonizing to traditional patterns ( UPGRADE, 2002 ) .
Knowledge is a cardinal to intelligent behaviour and, hence, ITSs are said to be knowledge-based because they have: ( I ) sphere cognition, ( two ) cognition about learning rules and about methods for using those rules, and ( three ) cognition about methods and techniques for pupil mold ( S. Stankov et al. , 2007 )
It is of import to observe that ITS is an interdisciplinary field that investigates how to invent educational systems that provide direction tailored to the demands of single scholars, as many good instructors do ( Conati et al. , 2002 )
There are three types of cognition that an intelligent coach ( human or unreal ) needs to hold to be able to help pupil acquisition: ( I ) cognition about the mark instructional sphere, ( two ) cognition about the pupil, and ( three ) cognition about the relevant pedagogical/instructional schemes.
5. Mobile Intelligent Tutoring System
Harmonizing to Brown ( 2009 ) , Mobile ITSs have non received extended research. There has been small research aimed at placing how to accommodate the desktop coachs and which facets of the coach to alter, as facets of desktop coachs require alteration for nomadic device content bringing.
The bringing of ITSs on nomadic devices in Kenya has the possible to supply the important advantages of intelligent tutoring systems to a wider audience of scholars therefore assisting in bridging the digital divide.
Some secondary schools provide Internet and computing machine entree to pupils but a deeper appraisal reveals that the presence of engineering does non compare to effectual usage of the engineering ( Yong et al, 2006 ) . Among the several factors impeding usage is the student-to-computer ratio in schools. For those schools with computing machines, it is reported that no school has one computing machine for each pupil with the lowest computer-to-student ratio being about 3-to-1 ( Christopher et al, 2007 ) . On the other manus, about all pupils can entree the nomadic phones doing it possible for schools to do usage of handheld calculating to organize engineering usage between place and school for the pupils. This tendency is besides nailing of the possible that nomadic and hand-held devices have to present a one-to-one calculating solution to the instruction community ( Quinn, 2000 ) .
By utilizing nomadic devices, schools without the fiscal resources to put in and keep big computing machine labs can hold the ability to supply scholars with ITS engineering. One singular virtue is that pupils can easy transport the coachs between place and school besides sharing the nomadic ITSs between pupils in the same school therefore enabling ‘everywhere ‘ and ‘anytime ‘ acquisition ( Facer, Faux, McFarlane, 2005 ) . The portability of nomadic ITSs extends coach usage to exterior of computing machine labs and traditional schoolrooms, thereby supplying flexible larning chances to pupils at place, after school, and in other locations ( Vahey et Al, 2004 ) . With the promotion of nomadic device engineering, there is besides the possibility for nomadic ITSs to put to death as standalone applications, as opposed to client-server web based, thereby extinguishing the demand for an Internet connexion, either wired or radio.
Harmonizing to the research conducted by Brown ( 2009 ) to find whether nomadic intelligent tutoring system provide larning additions greater than standard instructional activities, it was found out that pupils utilizing the tutoring status did see an addition in post-test public presentation greater than pupils that did non utilize the coach ( utilizing paper and pencil ) . As a consequence, it can be concluded that a nomadic ITS can supply larning additions greater than standard direction.
6. Related Work
In the early 1970s a few research workers defined a new end for computer-based direction. They adopted the human coach as their educational theoretical account and sought to use unreal intelligence techniques to recognize this theoretical account in “ intelligent ” computer- based direction.
Personal human coachs provide a extremely efficient larning environment ( Cohen and Kulik, 1982 ) and have been estimated to increase average achievement results by every bit much as two Intelligent Tutoring Systems standard divergences ( Bloom, 1984 ) . The end of ITSs would be to prosecute the pupils in sustained logical thinking activity and to interact with the pupil based on a deep apprehension of the pupils ‘ behaviour.
From 1990s, research on teaching method in the mathematics recognized that pupils learn mathematics more efficaciously, if the traditional acquisition of expressions and processs is supplemented with the possibility to research a wide scope of jobs and job state of affairss through ITS ( Schoenfeld, 1990 ) . In peculiar, the international comparative survey of mathematics learning ( Baumert et al. , 1997 ) , has shown that learning with an orientation towards active job work outing outputs better larning consequences in the sense that the acquired cognition is more readily available and applicable particularly in new contexts and that a contemplation about the job work outing activities and methods outputs a deeper apprehension and better public presentation.
Harmonizing to James and Sowmya ( 2006 ) , Carnegie Learning developed a suite of ITSbased “ cognitive coachs ” in secondary-level mathematics. The systems, based on earlier research carried out by John Anderson and Ken Koedinger at Carnegie Mellon University, were tested in selected secondary school and pupils showed 50- to 100-percent betterment in job resolution and usage of equations, tabular arraies, and graphs.
Eric and Jorg ( 2003 ) developed ActiveMath ITS used in job resolution, rule-based systems, cognition representation, user mold, adaptative systems and adaptative hyper-media, and diagnosing.
ALEKS ( Assessment and Learning in Knowledge Spaces ) is an on-line ITS aimed at tutoring Geometry and Business Mathematics classs ( Anderson, Reder, Simon, 1996 ) . It is web based and therefore requires Internet connexion for it to be accessed.
MathITS ( Korhan, 2006 ) is an Intelligent Tutoring System for mathematics instruction at undergraduate and graduate degree and employs the conceptual map mold technique ( Hwang, 2003 ) . It is a student-centred system, which supports synergistic acquisition.
7. Challenges Faced in Developing Mobile ITS Applications for Mathematics Tutoring
It is easier said than done for teachers, school decision makers, and even parents to see nomadic devices as being utile for educational intents because they have been predominately used for societal intents including phone communicating and text messaging. The current educational system produces lesson programs, larning activities, and appraisals based upon traditional educational theoretical accounts. However, the debut of nomadic devices enables pupils to interact and join forces with one another in ways non antecedently realized. Therefore, teachers must now find how to plan lessons and activities structured around this mobility and accurately quantify the consequences of the usage of the engineering.
The usage of nomadic devices besides raises inquiries that relate to the execution of the engineering, viz. the hardware and package. Previous tests of nomadic larning applications reveal that concerns sing device ownership, battery life, and web connectivity can greatly impact the acquisition results of pupils ( Facer, Faux, and McFarlane, 2005 ) . While these issues may be viewed by some as policy instead than research, it can be argued that an apprehension of these issues could supply information to inform the design of the applications themselves. For illustration, cognizing that pupils may non hold dependable Internet connexions may do a interior decorator to make a standalone application or one that requires periodic synchronism for it to work decently.
Interestingly, research workers implementing and proving nomadic larning applications have noted that there is possible for nomadic larning applications to be alongside traditional instructional tools ( Vahey et al. , 2004 ) . While the usage of nomadic larning applications can be transformative, it is necessary to understand and see the bing acquisition environment in which it is intended. While there are surely cases in which a Mobile larning application can supply an experience non possible without the engineering ( Chen, Kao and Sheu, 2003 ) , it seems sensible, and even likely, that this engineering can co-exist and back up traditional paper-based methods.
Representation of diagrams and limited sum of text poses a challenge. As a consequence, the teachers should make up one’s mind on which content could best be presented in nomadic device. The diagrams representation is limited by screen size.
Mobile ITS execution will assist to better mathematics public presentation in Kenya Secondary schools. However, certain research countries such as its development, statute law issues, interface, instruction and acquisition schemes and architecture ( hardware and package ) should be addressed in order to recognize the benefits of Mobile ITS. By so making, Kenya will tout of m-Learning and therefore will make more pupils assisting to bridge the digital divide spread.
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