Effectiveness of the TM Intranet Website

The purpose of this research is to study the effectiveness of the TM online information website in achieving the desired information dissemination in order for the staffs to acquire the necessary knowledge. The aims are to identify the effectiveness of the TM Intranet website and to provide recommendations for the future improvement of the system. In this study, staffs using the TM Intranet environment daily at their work premises were surveyed through online survey to evaluate the intranet system. About 50 staffs were targeted to participate and the respondents were only 42. Results showed that there are three main factors that influence the effectiveness of the TM Intranet website in relation to their daily work. These factors are staffs’ behavior and attitude, technology and system, and interactive applications. The paper discusses these factors in detail with an emphasis on the role of the TM Intranet website in information and knowledge dissemination for the staff in their daily work environment

Factors Which Influence Key Entry Speed On Hard and Soft Keyboards: Experience, Eye Behaviors and Finger Movements

Soft keyboards have become ubiquitous, especially with the introduction of the iPad. This study aims to determine for experienced touch typists whether there are characteristics of soft QWERTY keyboards that can make them easier to use and why those characteristics provide an advantage. Two characteristics would appear to be of central importance. First, hard keyboards provide home row positioning information that is not as easily provided by soft keyboards. Second, hard keyboards also provide auditory and tactile feedback when a key is depressed, something not generally provided with soft keyboards. In order to test the hypothesis that the absence of home row positioning and key strike feedback information can reduce expert touch typists’ speeds on soft keyboards, expert touch typists were run in two experiments. In Experiment 1, soft and hard keyboards in landscape and portrait mode were evaluated. The hard keyboards had the standard home row positioning and key strike feedback whereas the soft keyboards had neither. If these are important elements in typing speed, then experienced hard keyboard typists should type less quickly when using soft keyboards than when using hard keyboards. Moreover, if reducing the footprint of the keyboard, from landscape to portrait, requires more eye movements, then typists using both hard and soft keyboards should be slower when using the portrait size keyboard than when using the landscape size keyboard. Perhaps not surprisingly, experienced hard keyboard touch typists do less well when entering information on soft keyboards without home row positioning information or auditory feedback. Moreover, both groups appear to type more slowly in keyboards laid out in a portrait format than they do in keyboards laid out in a landscape format. In summary, the results from Experiment 1 suggest that both home row positioning information and auditory key strike feedback should speed performance. In Experiment 2, an attempt was made to determine just how much of a gain can be made in the typing speed of more experienced soft keyboard users if home row positioning information (tactile feedback), auditory feedback, or both are added. Participants were run in four conditions: auditory key strike feedback (with and without) was crossed with tactile home row positioning information (with and without). Participants included expert level hard keypad QWERTY touch typists who have had at least five hours’ typing experience with an iPad. Participants were given four passages to type, all of equal length and all balanced for letter frequency. Participants typed one passage in each of the four conditions. The passage sequence was counterbalanced across participants. Typing speeds for each of the passages was measured and averaged across participants within conditions. A repeated measures analysis of variance was used to determine whether there was a main effect of position or feedback. In order to determine why it is that home row positioning and key strike feedback alters performance, eye behaviors, movement times and task completion times are calculated. If home row position information is important, soft keyboards without this information may have a larger number of glances that a typist directs at the keyboard. These glances will help the typist determine either whether a finger is positioned over the correct home key (the launch key) or whether the location of the key to be typed next (the target key) is in the expected position. If key strike feedback is important, soft keyboards without this information should have longer movement times where the typists do not need to glance at the keyboard. This follows since the typist will process less quickly the fact that a finger has landed on a key. Key press and key release times will be included each time a character, number or spacebar is depressed or releases. The finger movement time between any pair of keys i and j will be derived from the key press and key release times. This time will be measured from the moment the finger leaves the launch key i until the moment that the finger arrives at the target key j. Task completion times were defined as the difference between the first key press in a passage and the last key release. Finger movement times, inter-keystroke intervals and task completion times were recorded using a program developed in JAVA 2SE. Eye movements are recorded with aid of an ASL Mobile EYE tracker. Analyses of the finger movement times and task completions times in Experiment 2 indicated that participants were fastest when both position information and auditory feedback were included. When just finger movement times are considered, there was a significant effect of auditory feedback but not of positioning information. This was what was expected given that the speed of finger movement times is arguably largely a function of how quickly a typist perceives that a movement has been completed, something that auditory feedback, but not positioning information provides. When just the task completion times were analyzed, position information had a significant effect. The effect of auditory feedback was only marginally significant. It was expected that both factors would be significant. Perhaps the power was too small. Finally, when the eye movements were analyzed, the total scanning time was shortest when both position information and auditory feedback were available. The effects of both were statistically significant. In summary, on the basis of the results from Experiment 1 it appeared likely that auditory feedback and positioning information accounted in part for the faster typing times of touch typists on hard keyboards as opposed to soft keyboards. In Experiment 2, this hypothesis was evaluated. Finger movement and task completion times were fastest when both auditory feedback and positioning information were present. The effect of auditory feedback appeared to impact only the finger movement times. The effect of both auditory feedback and positioning information appeared to impact the task completion times. However, the effect of auditory feedback on task completion times was only marginal. Finally, it was clear that much of the reduction in task completion times occurred because the time that the touch typists spent scanning the keyboard was smaller when both auditory feedback and positioning information was available. It is recommended in the future that soft keyboards have both sets of feedback available, auditory (through simulated key clicks) and tactile (through home row positioning information). The gains in typing speed with these additions were models (about 10%), considered over the entire population of users the impact could be considerable

Modèle théorique et outil de simulation pour une meilleure évaluation des claviers logiciels augmentés d'un système de prédiction de mots

Les claviers logiciels se sont démocratisés pour rendre possible la saisie de textes en mobilité sur des dispositifs dépourvus de claviers physiques tels que les téléphones portables nouvelle génération. Cependant, ces claviers présentent plusieurs inconvénients comme la lenteur de la saisie et la fatigue engendrées pour les utilisateurs déficients moteurs. La solution intuitive était d'allier ces logiciels à des listes contenant les mots susceptibles de continuer la saisie d'un mot initié par l'utilisateur. Bien que ces listes, dites listes de prédiction, réduisent le nombre de clics et le nombre d'opérations, la vitesse de saisie de l'utilisateur a diminué. Une expérimentation outillée d'un système de suivi du regard a ainsi permis de déterminer des " stratégies " de fonctionnement de l'utilisateur face à une liste de mots. Ces résultats ont ainsi permis d'affiner les modèles de prédiction de manière à réduire l'écart séparant les performances prédites des performances réellement enregistrées. A partir des constats effectués lors de la première expérimentation, nous proposons deux variantes de l'utilisation des listes de prédiction de mots. La première propose un nouveau moyen d'interagir avec la liste de mots et permet ainsi de maximiser l'utilisation de celle-ci. La seconde évalue un repositionnement de la liste de mots de manière à réduire le nombre de mouvements oculaires vers la liste. Ces deux évolutions, évaluées théoriquement puis au moyen d'une expérimentation utilisateur, permettent ainsi d'améliorer les performances de saisie par rapport à une liste de prédiction de mots classique.Predictive model and simulation tool for a best evaluation of soft keyboard augmented by words prediction list The software keyboards are used to enable text input in mobility and for devices without physical keyboards, such as the new generation of mobile phones. However, these keyboards have several drawbacks such as slowness text entry and fatigue generated for motor impaired users. The solution was to combine software keyboard to lists containing the words likely to continue the word introduced by the user. While these lists, so-called prediction lists, reduce the number of clicks and the number of operations, the speed of user input has decreased. An experiment with an eye tracking system has identified the "strategies" of the user while using and searching a list of words. These results were helpful to refine the prediction models in order to reduce the gap between the performance predicted and the performance actually recorded. Based on observations made during the first experiment, we propose two variants of the use of word prediction list. The first proposes a new way to interact with the list of words and allows maximum use of it. The second evaluates a repositioning of the list of words in order to reduce the number of eye movements to the list. These two propositions were theoretically and experimentally evaluated by users. These software can improve the input performances compared with a classic word prediction list

Computational optimization and prediction strategies for increasing communication rate in phoneme-based augmentative and alternative communication (AAC)

Up to 1.2% of the population is unable to meet daily communication needs using typical speech and may use augmentative and alternative communication (AAC) strategies to communicate, including manual sign language, facial gestures, and aided strategies such as selecting targets on an onscreen keyboard. However, for individuals whose impairments affect both speech and non-speech motor systems (e.g., spinal cord injury, amyotrophic lateral sclerosis, multiple sclerosis), their ability to use manual sign and access computer systems are impacted. AAC access methods in this population remain inherently slow and effortful (e.g., eye-tracking, head-tracking, mechanical switches). Thus, optimizing communication interfaces for alternate access methods may provide significant improvements in communication rates and quality of life. In this series of studies, we developed and evaluated methods for improving communication rates through optimization and prediction in communication interfaces. These interfaces enabled participants to select sounds (phonemes) instead of letters and were computationally optimized offline via a model of human movement in order for targets likely to be selected together to be in close proximity. Online prediction was implemented such that likely targets were dynamically enlarged. Computational simulations suggested that optimized phonemic interfaces could increase communication rates by up to 30.9% compared to random phonemic interfaces. Communication rates were empirically evaluated in 36 participants without motor impairment using an alternate computer access method to produce messages with phonemic interfaces over 12 sessions. Results suggested that optimization increased communication rates by 10.5–23.0% compared to a random phonemic interface. Prediction increased communication rates during training sessions, but was not a significant factor in communication rates during the final session. Empirical evaluations in individuals with motor impairment revealed that all participants strongly agreed that they would improve with practice, and four out of six participants strongly preferred the interface with prediction. Results of these studies suggest that optimized and predictive phonemic interfaces may provide increased communication rates for individuals with motor impairments affecting both oral communication and computer access. Methods for dynamically enlarging targets may also be applicable to other (non-phonemic) interfaces to increase communication rates. Further research is needed to fully translate these results into clinical practice.2020-10-24T00:00:00

Chinese Text Entry with Mobile Devices

Tietokoneiden ja nykyaikaisten matkapuhelimien käytön kannalta on olennaista, että niihin voidaan syöttää tekstiä tehokkaasti. Kiinan kielen eri murteita puhuu äidinkielenään noin viidesosa maailman väestöstä eli yli miljardi ihmistä. Kiinan kielen merkki- ja tavuperustaisuus tekee siitä tekstinsyötön kannalta ainutlaatuisen haastavan. Monet kiinalaisista merkeistä ovat rakenteeltaan monimutkaisia ja homofonisia (ääntyvät samalla tavoin) joidenkin muiden merkkien kanssa. Syötettäessä tekstiä näppäimistöltä tavallinen tapa on käyttää ns. pinyin-koodeja, joiden avulla kukin kiinan merkki voidaan esittää useasta latinalaisen aakkoston merkistä koostuvana koodina. Homofoniasta johtuen tarkoitettu kiinan kielen merkki joudutaan tämän jälkeen vielä valitsemaan usean vaihtoehdon joukosta, mikä tekee tekstinsyöttöprosessista vaikeampaa kuin romaanisten kielten tapauksessa. Lisäksi on otettava huomioon Kiinan eri osissa puhutut useat murteet. Kaikki nämä tekijät yhdessä tekevät kiinankielisen tekstin syötöstä tietokoneille haastavaa. Tämän väitöskirjan tavoitteena on parantaa kiinankielisen tekstin syöttötapojen käyttäjäkokemusta käytettäessä matkapuhelimia ja muita mobiililaitteita. Väitöskirjassa tutkitaan empiiristen kokeiden ja mallinnuksen avulla uusia tekstinsyöttötapoja ja niiden käyttöä. Tutkimuksen kohteena on neljä erilaista tekstinsyöttötapaa: kiinankielen käsinkirjoituksen tunnistus, pyörivän kiekon avulla tapahtuva tekstinsyöttö, mandariinikiinaan perustuva sanelu, ja numeronäppäinten avulla tapahtuva pinyin-koodien syöttö. Työssä ehdotetaan uusia tekniikoita sekä käsinkirjoituksen tunnistukseen että kiekkoa käyttävään pinyin-koodien syöttöön. Empiirisissä kokeissa osoittautui että käyttäjät pitivät uusista tekniikoista. Mandariinikiinalle on suunniteltu lyhytviestien sanelusovellus, josta on tehty kaksi käyttäjäkoetta. Myös numeronäppäinten avulla tapahtuvaa pinyin-koodien syöttöä on tutkittu kahdessa kokeessa. Ensimmäisessä kokeessa vertailtiin viittä eri menetelmää. Se tuotti suunnitteluohjeita etenkin koskien fraasien (useamman merkin kokonaisuuksien) syöttöä, tekniikkaa joka voi nopeuttaa tekstinsyöttöä. Toisen osatutkimuksen tuloksena on tekstinsyöttöä kuvaava malli, jonka avulla voidaan ennustaa menetelmän nopeutta kun syötettäessä ei tehdä virheitä. Tutkimus johti myös useisiin jatkotutkimuskysymyksiin. On tarpeen kehittää tehokkaampia menetelmiä tilanteeseen, jossa merkki joudutaan valitsemaan useista vaihtoehdoista. Kehityspotentiaalia on myös merkkien perustana olevien viivojen tunnistustavoissa sekä kosketusnäytöllä esitettyjen näppäimistöjen paremmassa hyödyntämisessä.For using computers and modern mobile phones it is essential that there are efficient methods for providing textual input. About one fifth of the world´s population, or over one billion people, speaks some variety of Chinese as their native language. Chinese has unique characteristics as a logosyllabic language. For example, many Chinese characters are complex in structure and normally homophonic with some others. With keyboards and other key-based input devices the normal approach is to use so-called pinyin input, where the Chinese characters are entered using their pinyin mark that consists of several characters in the Roman alphabet. Because of homophony this technique requires choosing the correct Chinese character from a list of posssible choices, making the input process more complicated than in Roman languages. Moreover, the many varieties of the language in different parts of China have to be taken into account as well. All above factors bring new challenges to the design and evaluation of Chinese text entry methods in computing systems. The overall objective of this dissertation is to improve user experience of Chinese text entry on mobile devices. To achieve the goal, the author explores new interaction solutions and patterns of user behavior in the Chinese text entry process with various approaches including empirical studies and performance modeling. The work covers four means of Chinese text entry on mobile devices: Chinese handwriting recognition, Chinese indirect text entry with a rotator, Mandarin dictation, and Chinese pinyin input methods with a 12-key keypad. New design solutions for Chinese handwriting recognition and pinyin methods utilizing a rotator are proposed and proved being well accepted by users with empirical studies. A Mandarin short message dictation application for mobile phones is also presented , with two associated studies on human factors. Two studies were also carried out on Chinese pinyin input methods that are based on the 12-key keypad. The comparative study of five phrasal pinyin input methods led to design guidelines for the advanced feature of phrasal input. The second study of pinyin input methods produced a predictive model addressing users´ error-free speeds. Based on the conclusions from studies in this thesis, several additional research questions were identified for the future. For example, improvements are necessary to promote user performance on target selection process in Chinese text entry on mobile devices. Moreover, design and studies on stroke methods and Chinese specific soft keyboards are also required

Predicting Endpoint of Goal-Directed Motion in Modern Desktop Interfaces using Motion Kinematics

Researchers who study pointing facilitation have identified the ability to identify--during motion--the likely target of a user's pointing gesture, as a necessary precursor to pointing facilitation in modern computer interfaces. To address this need, we develop and analyze how an understanding of the underlying characteristics of motion can enhance our ability to predict the target or endpoint of a goal-directed movement in graphical user interfaces. Using established laws of motion and an analysis of users' kinematic profiles, we demonstrate that the initial 90% of motion is primarly balistic and submovements are limited to the last 10% of gesture movement. Through experimentation, we demonstrate that target constraint and the intended use of a target has either a minimal effect on the motion profile or affects the last 10% of motion. Therefore, we demonstrate that any technique that models the intial 90% of gesture motion will not be affected by target constraint or intended use. Given, these results, we develop a technique to model the initial ballistic motion to predict user endpoint by adopting principles from the minimum jerk principle. Based on this principle, we derive an equation to model the initial ballistic phase of movement in order to predict movement distance and direction. We demonstrate through experimentation that we can successfully model pointing motion to identify a region of likely targets on the computer display. Next, we characterize the effects of target size and target distance on prediction accuracy. We demonstrate that there exists a linear relationship between prediction accuracy and target distance and that this relationship can be leveraged to create a probabilistic model for each target on the computer display. We then demonstrate how these probabilities could be used to enable pointing facilitation in modern computer interfaces. Finally, we demonstrate that the results from our evaluation of our technique are supported by the current motor control literature. In addition, we show that our technique provides optimal accuracy for any optimal accuracy when prediction of motion endpoint is performed using only the ballistic components of motion and before 90% of motion distance

An analysis of interaction in the context of wearable computers

The focus of this thesis is on the evaluation of input modalities for generic input tasks, such inputting text and pointer based interaction. In particular, input systems that can be used within a wearable computing system are examined in terms of human-wearable computer interaction. The literature identified a lack of empirical research into the use of input devices for text input and pointing, when used as part of a wearable computing system. The research carried out within this thesis took an approach that acknowledged the movement condition of the user of a wearable system, and evaluated the wearable input devices while the participants were mobile and stationary. Each experiment was based on the user's time on task, their accuracy, and a NASA TLX assessment which provided the participant's subjective workload. The input devices assessed were 'off the shelf' systems. These were chosen as they are readily available to a wider range of users than bespoke inpu~ systems. Text based input was examined first. The text input systems evaluated were: a keyboard,; an on-screen keyboard, a handwriting recognition system, a voice 'recognition system and a wrist- keyboard (sometimes known as a wrist-worn keyboard). It was found that the most appropriate text input system to use overall, was the handwriting recognition system, (This is forther explored in the discussion of Chapters three and seven.) The text input evaluations were followed by a series of four experiments that examined pointing devices, and assessed their appropriateness as part of a wearable computing system. The devices were; an off-table mouse, a speech recognition system, a stylus and a track-pad. These were assessed in relation to the following generic pointing tasks: target acquisition, dragging and dropping, and trajectory-based interaction. Overall the stylus was found to be the most appropriate input device for use with a wearable system, when used as a pointing device. (This isforther covered in Chapters four to six.) By completing this series of experiments, evidence has been scientifically established that can support both a wearable computer designer and a wearable user's choice of input device. These choices can be made in regard to generic interface task activities such as: inputting text, target acquisition, dragging and dropping and trajectory-based interaction.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Méthodologie et instrumentalisation pour la conception et l'évaluation des claviers logiciels

Avec l'expansion des dispositifs mobiles, l'efficacité de la saisie de texte est un défi de plus en plus important pour l'interaction homme-machine. Or, nous observons que, bien que les claviers type AZERTY ou téléphone, traditionnellement utilisés sur ces supports, soient évalués comme sous-optimaux, et, bien que de nombreuses alternatives évaluées comme plus performantes soient proposées dans la littérature, ces nouvelles alternatives restent très marginalement utilisées. Sur la base de cette observation, nous argumentons que la finalité des évaluations ne tient compte que d'un aspect du clavier, aspect qui n'est pas représentatif de la capacité d'un utilisateur à intégrer les concepts proposés dans son quotidien. Nous proposons en conséquence une stratégie complémentaire d'évaluation sur la base d'une évaluation heuristique des claviers logiciels. Par ailleurs, de manière à faciliter la mise en œuvre des évaluations et simplifier le design de nouveaux claviers, nous proposons une nouvelle version (E-Assist II) de la plate-forme E-Assiste. Elle permet, en premier lieu, de facilité le design et le déroulement des expérimentations, et plus largement d'encadrer les évaluations théoriques, expérimentales et heuristiques des claviers. Une version TinyEAssist permet également de déployer des expérimentations sur des supports mobiles (téléphones portables notamment). En second lieu, sur la base de l'étude de la structure des claviers logiciels, nous avons de plus proposé un langage de spécification des claviers permettant de générer des claviers logiciels complexes (interagissant potentiellement avec des systèmes de prédiction) à des fins d'expérimentation ou de simple usage. Enfin, sur la base des critères de performance mis en évidence par les évaluations heuristiques, nous proposons quatre nouveaux paradigmes de claviers. Parmi ces paradigmes deux ont offert des perspectives particulièrement intéressantes : en premier lieu le clavier multi-layer consistant à conduire progressivement, au cours d'une période transitoire, un utilisateur d'une distribution de touches type AZERTY vers une distribution de touches optimisée ; Le second consistant à faciliter l'accès aux caractères type accents, majuscules ou ponctuation, souvent déconsidérés dans l'optimisation des claviers logiciels.The expansion of mobile devices turn text input performances a major challenge for Human-Machine Interaction. We observed that, even if traditional QWERTY soft keyboards or telephone based soft keyboard were evaluated as poorly efficient, and, even if several alternatives evaluated as more efficient were proposed in the research field, these new alternatives are rarely used. Based on this observation, we argue that the goal of soft keyboard evaluation focus on long term performances whereas does not take into account the perspective for a user to use it in his quotidian. Consequently, we propose a complementary evaluation strategy base on heuristic evaluation methodology. In order to ease the evaluation and design of new soft keyboards, we proposed a new version (E-Assist II) of the E-Assiste plate-form. This plate-form aims, at first, to facilitate the design and procedure of experimentations and, more generally, to guide the theoretical, experimental and heuristic evaluations. A compact version (TinyEAssist) enables to perform experimentation on mobile environment such as mobile phone. At second, based on soft keyboard structure study, we proposed a keyboard specification language enabling to generate complex keyboard (including soft keyboard interacting with prediction systems). The generated soft keyboards may be used into the experimentation plate-form or interacting with the exploration system. At last, based on the criteria highlighted by the heuristic evaluation, we proposed four new soft keyboard paradigms. Among them two paradigms showed interesting perspectives: at first the multilayer keyboard consist in accompanying the user from a standard QWERTY layout to an optimized layout during a transition period; the second consist in accelerating the access to the characters such as accents, upper-case, punctuation, etc., frequently ignored in the keyboard optimizations