Abstract: Industry 4.0 is the fourth industrial revolution that focuses on interconnectivity of machine to machine, human to machine and human to human via Internet of Things (IoT). Technologies of industry 4.0 facilitate communication between human and machine through IoT and forms Cyber-Physical Production System (CPPS). In CPPS, multiple shop floors sensor data are connected through IoT and displayed through sensor dashboard to the operator. These sensor dashboards have enormous amount of information to be presented which becomes complex for operators to perform monitoring, controlling and interpretation tasks. Designing handheld sensor dashboards for supervision task will become a challenge for the interface designers. This paper reports emerging technologies of industry 4.0, changing context of increasing information complexity in consecutive industrial revolutions and upcoming design challenges for interface designers in context of Industry 4.0. Authors conclude that information complexity of sensor dashboards design has increased with consecutive industrial revolutions and designs of sensor dashboard causes cognitive load on users. Designing such complex dashboards interfaces in Industry 4.0 context will become main challenges for the interface designers.
Abstract: Programming is one of the challenging subjects in the field of computing. In the higher education sphere, some programming novices’ performance, retention rate, and success rate are not improving. Most of the time, the problem is caused by the slow pace of learning, difficulty in grasping the syntax of the programming language and poor logical skills. More importantly, programming forms part of major subjects within the field of computing. As a result, specialized pedagogical methods and innovation are highly recommended. Little research has been done on the potential productivity of the WhatsApp platform as part of a blended learning model. In this article, the authors discuss the WhatsApp group as a part of blended learning model incorporated for a group of programming novices. We discuss possible administrative activities for productive utilisation of the WhatsApp group on the blended learning overview. The aim is to take advantage of the popularity of WhatsApp and the time students spend on it for their educational purpose. We believe that blended learning featuring a WhatsApp group may ease novices’ cognitive load and strengthen their foundational programming knowledge and skills. This is a work in progress as the proposed blended learning model with WhatsApp incorporated is yet to be implemented.
Abstract: New sensors and technologies – such as microphones,
touchscreens or infrared sensors – are currently making their
appearance in the automotive sector, introducing new kinds of
Human-Machine Interfaces (HMIs). The interactions with such tools
might be cognitively expensive, thus unsuitable for driving tasks.
It could for instance be dangerous to use touchscreens with a
visual feedback while driving, as it distracts the driver’s visual
attention away from the road. Furthermore, new technologies in
car cockpits modify the interactions of the users with the central
system. In particular, touchscreens are preferred to arrays of buttons
for space improvement and design purposes. However, the buttons’
tactile feedback is no more available to the driver, which makes
such interfaces more difficult to manipulate while driving. Gestures
combined with an auditory feedback might therefore constitute an
interesting alternative to interact with the HMI. Indeed, gestures can
be performed without vision, which means that the driver’s visual
attention can be totally dedicated to the driving task. In fact, the
auditory feedback can both inform the driver with respect to the task
performed on the interface and on the performed gesture, which might
constitute a possible solution to the lack of tactile information. As
audition is a relatively unused sense in automotive contexts, gesture
sonification can contribute to reducing the cognitive load thanks
to the proposed multisensory exploitation. Our approach consists
in using a virtual object (VO) to sonify the consequences of the
gesture rather than the gesture itself. This approach is motivated
by an ecological point of view: Gestures do not make sound, but
their consequences do. In this experiment, the aim was to identify
efficient sound strategies, to transmit dynamic information of VOs to
users through sound. The swipe gesture was chosen for this purpose,
as it is commonly used in current and new interfaces. We chose
two VO parameters to sonify, the hand-VO distance and the VO
velocity. Two kinds of sound parameters can be chosen to sonify the
VO behavior: Spectral or temporal parameters. Pitch and brightness
were tested as spectral parameters, and amplitude modulation as a
temporal parameter. Performances showed a positive effect of sound
compared to a no-sound situation, revealing the usefulness of sounds
to accomplish the task.
Abstract: Personalized learning becomes increasingly popular which not be restricted by time, place or any other barriers. This study proposes an analysis of Personalized Learning using Item Response Theory which considers course material difficulty and learner ability.The study investigates twenty undergraduate students at TATI University College, who are taking programming subject. By using the IRT,it was found that, finding the most appropriate problem levels to each student include high and low level test items together is not a problem. Thus, the student abilities can be asses more accurately and fairly. Learners who experience more anxiety will affect a heavier cognitive load and receive lower test scores.Instructors are encouraged to provide a supportive learning environment to enhance learning effectiveness because Cognitive Load Theory concerns the limited capacity of the brain to absorb new information.
Abstract: The purpose of this study was to investigate the effects of computer–based instructional designs, namely modality and redundancy principles on the attitude and learning of music theory among primary pupils of different Music Intelligence levels. The lesson of music theory was developed in three different modes, audio and image (AI), text with image (TI) and audio with image and text (AIT). The independent variables were the three modes of courseware. The moderator variable was music intelligence. The dependent variables were the post test score. ANOVA was used to determine the significant differences of the pretest scores among the three groups. Analyses of covariance (ANCOVA) and Post hoc were carried out to examine the main effects as well as the interaction effects of the independent variables on the dependent variables. High music intelligence pupils performed significantly better than low music intelligence pupils in all the three treatment modes. The AI mode was found to help pupils with low music intelligence significantly more than the TI and AIT modes.
Abstract: Learning programming is difficult for many learners. Some researches have found that the main difficulty relates to cognitive load. Cognitive overload happens in programming due to the nature of the subject which is intrinisicly over-bearing on the working memory. It happens due to the complexity of the subject itself. The problem is made worse by the poor instructional design methodology used in the teaching and learning process. Various efforts have been proposed to reduce the cognitive load, e.g. visualization softwares, part-program method etc. Use of many computer based systems have also been tried to tackle the problem. However, little success has been made to alleviate the problem. More has to be done to overcome this hurdle. This research attempts at understanding how cognitive load can be managed so as to reduce the problem of overloading. We propose a mechanism to measure the cognitive load during pre instruction, post instruction and in instructional stages of learning. This mechanism is used to help the instruction. As the load changes the instruction is made to adapt itself to ensure cognitive viability. This mechanism could be incorporated as a sub domain in the student model of various computer based instructional systems to facilitate the learning of programming.
Abstract: The main purpose of the study was to determine whether students- interpretation achievement differed with the use of various multimedia presentation types. Four groups of students, text only (T), audio only (A), text and audio (TA), text and image (TI), were arranged and they were presented the same story via different types of multimedia presentations. Inference achievement was measured by a critical thinking inference test. Higher mean scores for the TA group compared to the other three groups were found. Also when compared pairwise, interpretation achievement of the TA group differed significantly from scores of the T and TI groups. These differences were interpreted with the increased cognitive load. Increased cognitive load for the TA group may have invited students to put more effort into comprehending the text, thus resulting in better test scores. Findings of the study can be seen as a sign of the importance of learning situations and learning outcomes in multimedia-supported learning environments and may have practical benefits for instructional designers.
Abstract: This paper describes part of a project about Learningby-
Modeling (LbM). Studying complex systems is increasingly
important in teaching and learning many science domains. Many
features of complex systems make it difficult for students to develop
deep understanding. Previous research indicates that involvement
with modeling scientific phenomena and complex systems can play a
powerful role in science learning. Some researchers argue with this
view indicating that models and modeling do not contribute to
understanding complexity concepts, since these increases the
cognitive load on students. This study will investigate the effect of
different modes of involvement in exploring scientific phenomena
using computer simulation tools, on students- mental model from the
perspective of structure, behavior and function. Quantitative and
qualitative methods are used to report about 121 freshmen students
that engaged in participatory simulations about complex phenomena,
showing emergent, self-organized and decentralized patterns. Results
show that LbM plays a major role in students' concept formation
about complexity concepts.
Abstract: E-learning is not restricted to the use of new technologies for the online content, but also induces the adoption of new approaches to improve the quality of education. This quality depends on the ability of these approaches (technical and pedagogical) to provide an adaptive learning environment. Thus, the environment should include features that convey intentions and meeting the educational needs of learners by providing a customized learning path to acquiring a competency concerned In our proposal, we believe that an individualized learning path requires knowledge of the learner. Therefore, it must pass through a personalization of diagnosis to identify precisely the competency gaps to fill, and reduce the cognitive load To personalize the diagnosis and pertinently measure the competency gap, we suggest implementing the formative assessment in the e-learning environment and we propose the introduction of a pre-regulation process in the area of formative assessment, involving its individualization and implementation in e-learning.
Abstract: A Web-based learning tool, the Learn IN Context
(LINC) system, designed and being used in some institution-s
courses in mixed-mode learning, is presented in this paper. This
mode combines face-to-face and distance approaches to education.
LINC can achieve both collaborative and competitive learning. In
order to provide both learners and tutors with a more natural way to
interact with e-learning applications, a conversational interface has
been included in LINC. Hence, the components and essential features
of LINC+, the voice enhanced version of LINC, are described. We
report evaluation experiments of LINC/LINC+ in a real use context
of a computer programming course taught at the Université de
Moncton (Canada). The findings show that when the learning
material is delivered in the form of a collaborative and voice-enabled
presentation, the majority of learners seem to be satisfied with this
new media, and confirm that it does not negatively affect their
cognitive load.
Abstract: Computer programming is considered a very difficult
course by many computer science students. The reasons for the
difficulties include cognitive load involved in programming,
different learning styles of students, instructional methodology and
the choice of the programming languages. To reduce the difficulties
the following have been tried: pair programming, program
visualization, different learning styles etc. However, these efforts
have produced limited success. This paper reviews the problem and
proposes a framework to help students overcome the difficulties
involved.
Abstract: In general, class complexity is measured based on any
one of these factors such as Line of Codes (LOC), Functional points
(FP), Number of Methods (NOM), Number of Attributes (NOA) and so on. There are several new techniques, methods and metrics with
the different factors that are to be developed by the researchers for calculating the complexity of the class in Object Oriented (OO)
software. Earlier, Arockiam et.al has proposed a new complexity measure namely Extended Weighted Class Complexity (EWCC)
which is an extension of Weighted Class Complexity which is proposed by Mishra et.al. EWCC is the sum of cognitive weights of
attributes and methods of the class and that of the classes derived. In EWCC, a cognitive weight of each attribute is considered to be 1.
The main problem in EWCC metric is that, every attribute holds the
same value but in general, cognitive load in understanding the
different types of attributes cannot be the same. So here, we are proposing a new metric namely Attribute Weighted Class Complexity
(AWCC). In AWCC, the cognitive weights have to be assigned for the attributes which are derived from the effort needed to understand
their data types. The proposed metric has been proved to be a better
measure of complexity of class with attributes through the case studies and experiments
Abstract: The purpose of this study was to investigate effects of
modality and redundancy principles on music theory learning among
pupils of different anxiety levels. The lesson of music theory was
developed in three different modes, audio and image (AI), text with
image (TI) and audio with image and text (AIT). The independent
variables were the three modes of courseware. The moderator
variable was the anxiety level, while the dependent variable was the
post test score. The study sample consisted of 405 third-grade pupils.
Descriptive and inferential statistics were conducted to analyze the
collected data. Analyses of covariance (ANCOVA) and Post hoc
were carried out to examine the main effects as well as the
interaction effects of the independent variables on the dependent
variable. The findings of this study showed that medium anxiety
pupils performed significantly better than low and high anxiety
pupils in all the three treatment modes. The AI mode was found to
help pupils with high anxiety significantly more than the TI and AIT
modes.
Abstract: Many difficulties are faced in the process of learning
computer programming. This paper will propose a system framework
intended to reduce cognitive load in learning programming. In first
section focus is given on the process of learning and the
shortcomings of the current approaches to learning programming.
Finally the proposed prototype is suggested along with the
justification of the prototype. In the proposed prototype the concept
map is used as visualization metaphor. Concept maps are similar to
the mental schema in long term memory and hence it can reduce
cognitive load well. In addition other method such as part code
method is also proposed in this framework to can reduce cognitive
load.