Online social network (OSN) is a platform, where users are able to share information among them easily and instantly. The sensitive information of an user can be misused by his/her friends or friends of friends due to the lack of reliable friend request acceptance (FRA), which is one of the key issues in OSNs. The existing FRA techniques are functioning based on either blind (i.e., without knowing information of a user, who sends the friend request to become a new friend, referred to as friend-to-be) or manual search method. Although, in the second method, the OSN user accepts a new friend based on his/her profile, however, it is not guaranteed that the profile is not fake. A approach is to bring down the misused information by filtering FRA using a reliable method to find out more information about the friend-to-be. This paper has proposed such a method for reliable decision making (RDM) of accepting friend request on OSNs in order to identify the attributes of a friend-to-be. RDM is a function with several parameters, such as security, flexibility, effectiveness, and satisfaction. To prove the reliability of the proposed method, an extensive quantitative study was carried out, which results indicated user's preferences for proposed method compared with the existing FRA methods.INDEX TERMS Friend request acceptance, online social networks (OSNs), reliable decision making.

The widespread adoption of technology-enhanced learning in various knowledge disciplines has pushed forward the development of information technology-assisted media for language learning and teaching. However, most of the existing electronic-learning (e-learning) solutions have underexplored and under-addressed given specific characteristics of grammar learning, which is one of the most demanding areas of language education. The lack of pedagogically informed instructional design to enhance learning performance on the current system can result in low motivation and engagement due to an imbalance and excessive increase of the cognitive load. This paper attempts to address these deficiencies posed by the existing systems by proposing smart communication networks that are driven by the student learning experience to manage cognitive load in the context of grammar learning. The e-grammar learning networks serve as a collaborative learning platform that combines a pedagogically informed instructional model named attention, relevance, confidence, and satisfaction (ARCS) and cyber interaction among teaching/learning agents. From the technological perspective, our numerical simulations demonstrate the desirable performance indicators of the proposed networks to facilitate information exchange and learning. From the education perspective, our empirical studies show that the overall smart network-enabled e-grammar learning system has desirable characteristics to motivate learners (m = 3.78) and manage their overall cognitive load (m =1.73), which suggest the promising capability of the proposed system.

Language learning is an emerging research area where researchers have done significant contributions by incorporating technological assistantship (i.e., computer-and mobileassistant learning). However, it has been revealed from the recent empirical studies that little attention is given on grammar learning with the proper instructional materials design and the motivational framework for designing an efficient mobile-assisted grammar learning tool. This paper hence, reports a preliminary study that investigated learner motivation when a mobile-assisted tool for tense learning was used. This study applied the Attention-Relevance-Confidence-Satisfaction (ARCS) model. It was hypothesized that with the use of the designed mobile-assisted tense learning tool students would be motivated to learn grammar (English tense). In addition, with the increase of motivation, performance outcome in paper-based test would also be improved. With the purpose to investigate the impact of the tool, a sequential mixed-method research design was employed with the use of three research instruments; Instructional Materials Motivation Survey (IMMS), a paperbased test and an interview protocol using a semi-structured interview. Participants were 115 undergraduate students, who were enrolled in a remedial English course. The findings showed that with the effective design of instructional materials, students were motivated to learn grammar, where they were positive at improving their attitude towards learning (male 86%, female 80%). The IMMS findings revealed that students' motivation increased after using the tool. Moreover, students improved their performance level that was revealed from the outcome of paper-based instrument. Therefore, it is confirmed that the study contributed to designing an effective multimedia based instructions for a mobile-assisted tool that increased learners' motivational attitude which resulted in an improved learning performance.

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The proliferation of modern mobile technologies on grammar learning (i.e., m-grammar learning) has generated a multitude of challenges in developing effective pedagogically-informed learning tools. The existing systems have mostly suffered from low motivation and poor learning effectiveness because of the three key reasons, namely: i) a weak tie to motivational theoretical principles, ii) a lack of proper instructional design, and iii) a lack of proper infrastructural design for data sharing between students and instructors. To deal with this issue, this paper presents MATT: a Mobile-Assisted Tense Tool that encapsulates an m-grammar instructional design leveraging upon cloud-fog-edge collaborative networking. Central to MATT is the incorporation of the Cognitive Theory of Multimedia Learning principles to minimize the extraneous cognitive load and a motivational model to increase motivation and learning effectiveness. To ensure effective instructional design, we exploit adaptive and dynamic approaches embodied in a flexible instructional paradigm that takes advantage of collective learning data exchange across cloud (central unit), fog (regional units) and edge (end devices/learners). To demonstrate the overall effectiveness of this system, we describe our findings in the evaluation of both the learning aspect (using a quantitative research design) and collaborative network performance (using numerical simulation). With an appropriate condition of delay-tolerant network-enabled learning data exchange, the results suggest that the students' cognitive load is low and motivational nature is high after using this system, which led them to perform more positively in the post-test evaluation.

Recent years online social networks (OSNs) have become an essential digital platform in the daily life of billions of earth inhabitants. Despite the advantages of easy communication and information sharing, OSNs users often fell in trouble causing by security breaches and violations. A recurring example of the troubles arises due to a rash acceptance of the friendship request, which can lead to the disclosure of personal information and vulnerability to an attack. Support for making a secure friendship decision is limited in the modern OSNs, making their use hazardous especially for the groups of children and young people. To overcome this issue, the paper proposes a method for evaluating the likelihood to become a friend in support of promoting hazard-free cyber environments. The proposed approach allows a user to define a model of a friend-to-be, and incoming friend requests are evaluated with reference to this model. The model takes into account the attributes (like common interests) and the behavioral properties of a friend-to-be (like frequency of the posts). The method allows for filtering friend requests to the given users and triggering notification of anomalous behaviors in an OSN. An empirical study proves the validity of the proposed model and its favorable characteristics against existing methods in the current OSN platforms.INDEX TERMS Online social network (OSN), friend request acceptance (FRA), decision making, recommender system, hazard-free cyber environment.

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In this paper, the concept of derivation is studied and its relation to English vocabulary learning is discussed. A structured based derivation process, which is an efficient way of enhancing English vocabulary compared to traditional vocabulary learning such as dictionary based and text based approaches, is proposed. This structural process helps to grow learners’ interest to build more words in a faster way. Such a dynamic and emergent approach of enriching English words truly emerges with its important implications for the teaching of English in language learning classes. In order to ensure the efficiency of this process, experimental design was employed to test learners’ ability to enhance their vocabulary knowledge. Thirty students participated in this study, and they were divided into an experimental group and two control groups, with the administration of pre-test and posttest. The treatment is a brief training on vocabulary enhancing methods (i.e., dictionary, text and derivation based learning). The results reveal that students who used the derivation based learning (55%) were able to enhance their vocabulary knowledge better compared to those who were exposed to dictionary based learning (13%) and text based learning (22%). The outcome confirms the effectiveness of derivation.