MeLOD

In the last few years, many applications for mobile devices have been developed to support learning experiences both in formal and informal contexts. One of the main limits of these applications concerns the development of learning materials suitable for mobile learning contexts. In fact, learning content must be usually prepared in advance by teachers and maintained during the whole lifespan of the application. In this paper, we present MeLOD, a mobile learning environment, which exploits the huge amount of dataset in the Linked Open Data (LOD) cloud to overcome the previous issue, and provides contextualized and continuously updated information based on students’ location. The position of the student sent by the mobile device is used to interlink Geonames DBpedia and Europeana datasets to provide information about all the interesting cultural heritage sites close to the student. Moreover, students social activities like voting and commenting are used to enhance the knowledge base of the environment and to provide recommendations for next students’ visits.

Reactivating Memories from a Mathematical Task over a Period of Sleep

Sleep, especially slow-wave sleep (SWS), has been found to facilitate memory consolidation for many types of learning. Mathematical learning, however, has seldom been examined in this context. Solving multiplication problems involves multiple steps before problems can be mastered or answers memorized, and thus it can depend on both skill learning and fact learning. Here we aimed to test the hypothesis that memory reactivation during sleep contributes to multiplication learning. To do so, we used a technique known as targeted memory reactivation (TMR), or the pairing of newly learned information with specific stimuli that are later presented during sleep. With TMR, specific memories can be reactivated over a period of sleep without disrupting ongoing sleep. We applied TMR during an afternoon nap to reactivate half of the multiplication problems that had previously been practiced. Results showed no effect of TMR on response time or accuracy of multiplication problem solving. Because these results were unexpected, we also used a variation of this paradigm to examine results in subjects who remained awake. Comparisons between the wake and sleep groups showed no difference in response time or accuracy in either the initial test or the final test. Although neither TMR nor sleep differentially influenced multiplication performance, correlational analysis provided some clues about mathematical problem solving and sleep. On the basis of these findings, even though they did not provide convincing support for our hypotheses, we suggest future experiments that could help produce a better understanding of the relevance of sleep and memory reactivation for this type of learning.

Supervised and unsupervised learning using a fully-plastic all-optical unit of artificial intelligence based on solitonic waveguides

The software implementations of neuronal systems have shown great effectiveness, even if the natural hardware separation between the processing and memory areas in computers slows down the analysis capacity. To overcome these limitations, new hardware configurations are moving towards neuromorphic models, capable of unifying the processing/memory dichotomy. Recently, integrated photonic X-junctions formed by waveguides written by spatial solitons have shown the ability to perform supervised learning. The solitonic technology, compared to the traditional one, offers the advantage of realizing plastic circuitry, a typical characteristic of biological neural networks. This work extensively studies both supervised and unsupervised learning of photonic soliton X-junctions. By exploiting the plasticity of the nonlinear refractive index at the base of the soliton formation, X-junctions can readdress their behaviours forwarding data to different outputs. In this article, we will extend the state-of-the-art: starting from supervised learning, for which all possible cases are now investigated, a material sensitive to the transported signals will be introduced to allow the junction to carry out unsupervised learning. In this way, the junction autonomously recognises the transported signals without the external intervention of the operator. Learning and memory now physically coincide in fact, learning means that the junction slowly switches based on the information sent; any further unknown information sent will find the junction in the modified state which corresponds to the learned information and will be recognised as well (reasoning based on comparison with stored information).

Predicting University Students’ Exam Performance Using a Model-Based Adaptive Fact-Learning System

Modern educational technology has the potential to support students to use their study time more effectively. Learning analytics can indicate relevant individual differences between learners, which adaptive learning systems can use to tailor the learning experience to individual learners. For fact learning, cognitive models of human memory are well suited to tracing learners’ acquisition and forgetting of knowledge over time. Such models have shown great promise in controlled laboratory studies. To work in realistic educational settings, however, they need to be easy to deploy and their adaptive components should be based on individual differences relevant to the educational context and outcomes. Here, we focus on predicting university students’ exam performance using a model-based adaptive fact-learning system. The data presented here indicate that the system provides tangible benefits to students in naturalistic settings. The model’s estimate of a learner’s rate of forgetting predicts overall grades and performance on individual exam questions. This encouraging case study highlights the value of model-based adaptive fact-learning systems in classrooms

EKSPLORASI AKTIVITAS KEHIDUPAN SEHARI-HARI ANAK NELAYAN DI DESA LOBUK UNTUK MENDUKUNG PEMBELAJARAN IPA KONTEKSTUAL

EXPLORATION OF FISHERMAN CHILDREN'S DAILY LIFE ACTIVITIES AT LOBUK VILLAGE TO SUPPORT CONTEXTUAL SCIENCE LEARNINGAbstractThe daily activities of fishermen's children can be used as a material context in applying contextual science learning, as emphasized by K13. In fact, learning science in coastal schools is not yet contextual to the daily activities of fishermen's children. This study aims to provide a description of the daily activities of fishermen's children in Lobuk Village, and a description of the relationship between these activities and science learning materials for SMP/MTs. This type of research is a descriptive qualitative case study method. The primary data sources were fishermen children aged SMP/MTs and their parents. Data collection techniques in the form of interviews, observation, and documentation. The results showed that fishermen's children's morning activities were helping with homework, preparing for school, then leaving for school. The daytime activity is helping the mother/aunt work in the drying process of the fish (a gherri jhuko'). The afternoon activity is looking for shells (arang-karang) during low tide, some of the shells are sold to earn pocket money or for parents, and some are used as salad. Nighttime activities are reciting/tarawih, tadarus, watching TV, then sleeping. The daily activities of fishermen children in their routine of helping to work a gherri jhuko’ and arang-karang in Lobuk Village are related to science learning materials for SMP/MTs, namely the classification of shells in Mollusca type invertebrates; the application of solid substance pressure to the knife for nyetak, mowang bunto ', and a gherri jhuko'. AbstrakAktivitas sehari-hari anak nelayan bisa digunakan sebagai konteks materi dalam menerapkan pembelajaran IPA kontekstual, sebagaimana penekanan K13. Faktanya, pembelajaran IPA di sekolah pesisir belum kontekstual terhadap aktivitas sehari-hari anak nelayan. Penelitian ini bertujuan untuk memberikan deskripsi aktivitas sehari-hari anak nelayan di Desa Lobuk, dan deskripsi keterkaitan aktivitas tersebut dengan materi pembelajaran IPA SMP/MTs. Jenis penelitian ini adalah deskriptif kualitatif dengan metode studi kasus. Sumber data primer dari anak-anak nelayan usia SMP/MTs beserta orang tua. Teknik pengumpulan data berupa wawancara, observasi, dan dokumentasi. Hasil penelitian menunjukkan aktivitas pagi hari anak nelayan adalah membantu pekerjaan rumah, menyiapkan diri ke sekolah, lalu berangkat sekolah. Aktivitas siang hari adalah membantu ibu/bibinya bekerja dalam proses pengeringan ikan (a gherri jhuko’). Aktivitas sore hari adalah mencari kerang (arang-karang) saat air laut surut, sebagian kerang dijual untuk menghasilkan uang jajan atau untuk orang tua, dan sebagian lagi dirujak. Aktivitas malam hari adalah mengaji/tarawih, tadarus, nonton TV, lalu tidur. Aktivitas sehari-hari anak nelayan dalam rutinitas membantu bekerja a gherri jhuko’ dan arang-karang di Desa Lobuk berkaitan dengan materi pembelajaran IPA SMP/MTs, yaitu pengklasifikasian kerang dalam avertebrata jenis Mollusca; penerapan tekanan zat padat pada pisau untuk nyetak, mowang bunto’, dan a gherri jhuko’.

Pengembangan Media Belajar Audiovisual Untuk Pembelajaran Memperbaiki Motor Listrik di SMK Negeri 1 Sarolangun

Learning process for repairing electricity motor competency at skill competency of Installation Electric Power Technique at SMK Negeri 1 Sarolangun has not been run effectively. In fact, learning material in repairing electricity motor just used modul as teaching materi and media learning. While, to get the competency thad needed, learning process should be supported by leaning tool well. For answer the problem above, teacher as a fasilitator in achievment of students competency is demanded to creative in learning management. One of them is by finding alternative solution that is by develop audiovisual media for learning of repairing electricity motor that can give solution in lerning process. Development of this media aim to product efective media in learning material of repairing electricity motor at SMK Negeri 1 Sarolangun. Development model that chosen is based on Borg and Gall model that adapted lerning design Dick and Carey model. Development process is done by 5 main steps: (1) Doing analysis, (2) Design pre product, (3) Validation and revision, (4) Try out at small scale field and, (5) Try out big group field. Based on the try out of audiovisual media for learning of repairing electricity motor at the SMK, responden give suggestion that the media can be benefit in learning process at school. The reason is that media can give information about the jobs steps clearly at matery of repairing electricity motor so give ease in learning. This ease in proved by the result of try out at big group that give conclution, there is increasingly at the result of study. There by, the media can comprehand learning material fast.

LEARNING ENGLISH TROUGH MUSIK IN THE DIGITAL AGE

This article aims to highlight the impact of music in teaching English as a second language. It discusses different approaches and techniques which can assist English language students to improve their learning skills by using technology. Special attention is paid to audio-lingual method and in particular to the role of songs in learning English. Music offers special benefits for those learning a new language. Listening to songs and singing is a natural and enjoyable way to practice new sounds, words, and phrases. In fact, learning a song or musical instrument is analogous in many ways to learning a language. Modern technology helps to provide students with music lessons. During these lessons instead of focusing on one single task for the entire study session, it is possible to mix things up: do listening, learn new vocabulary, then study grammar, read and write a short story on the same topic. The variety will keep the students engaged and make studying more fun. The authors suggest different types of activity to make lessons more effective. The extensive memorization, repetition and over-learning of patterns are the key to the method’s success.

On the Role of Weight Sharing During Deep Option Learning

The options framework is a popular approach for building temporally extended actions in reinforcement learning. In particular, the option-critic architecture provides general purpose policy gradient theorems for learning actions from scratch that are extended in time. However, past work makes the key assumption that each of the components of option-critic has independent parameters. In this work we note that while this key assumption of the policy gradient theorems of option-critic holds in the tabular case, it is always violated in practice for the deep function approximation setting. We thus reconsider this assumption and consider more general extensions of option-critic and hierarchical option-critic training that optimize for the full architecture with each update. It turns out that not assuming parameter independence challenges a belief in prior work that training the policy over options can be disentangled from the dynamics of the underlying options. In fact, learning can be sped up by focusing the policy over options on states where options are actually likely to terminate. We put our new algorithms to the test in application to sample efficient learning of Atari games, and demonstrate significantly improved stability and faster convergence when learning long options. 1

Is Machine Learning Real Learning?

The question of whether machine learning is real learning is ambiguous, because the term “real learning” can be understood in two different ways. Firstly, it can be understood as learning that actually exists and is, as such, opposed to something that only appears to be learning, or is misleadingly called learning despite being something else, something that is different from learning. Secondly, it can be understood as the highest form of human learning, which presupposes that an agent understands what is learned and acquires new knowledge as a justified true belief. As a result, there are also two opposite answers to the question of whether machine learning is real learning. Some experts in the field of machine learning, which is a subset of artificial intelligence, claim that machine learning is in fact learning and not something else, while some others – including philosophers – reject the claim that machine learning is real learning. For them, real learning means the highest form of human learning. The main purpose of this paper is to present and discuss, very briefly and in a simplifying manner, certain interpretations of human and machine learning, on the one hand, and the problem of real learning, on the other, in order to make it clearer that the answer to the question of whether machine learning is real learning depends on the definition of learning.

Pengembangan Bahan Ajar Ilmu Bayan Berbasis Analisis Kontrastif di Program Studi Pendidikan Bahasa Arab Sekolah Tinggi Ilmu Al-Quran

The students of Arabic Education at State Institute of Al-Qur’an study Ilmu Bayan in order to understand about the beauty and majesty of Al-Qur’an verses, language style, Arabic expression, and to compose the right and good sentences. But, in the fact, learning of Ilmu Bayan cannot comply all of those criterion. There are many problems in this case such as: Students have difficulties to remember the rules of Ilmu Bayan and they try to compare Ilmu Bayan study to Indonesian language study. The learned book is using Arabic language without any translation and it’s also dominated by Arabic poem which is difficult to understand. Based on those data, the researcher develops a teaching book based on contractive analysis.This research use qualitative and quantitative approach with research and development method. The result of this research are: 1 contrastive analysis between Ilmu Bayan style of language and Indonesian style of language, 2 Product, that is a teaching book of Ilmu Bayan for STIQ Amuntai students. So that the steps to arrange the book are: need analysis, collecting data, product design, validating product, revise product, expediency test of product, revise of expedience test of product, effectiveness test of product, revise product, 3 Teaching book arranged by researcher is effective in learning Ilmu Bayan, known by comparing control and experiment group posttest result, that is T counting (4,36) more than T table (1,71) and T table (2,42).