Query: online learning

title: DeepWalk: online learning of social representations
abstract: We present DeepWalk, a novel approach for learning latent representations of vertices in a network. These latent representations encode social relations in a continuous vector space, which is easily exploited by statistical models. DeepWalk generalizes recent advancements in language modeling and unsupervised feature learning (or deep learning) from sequences of words to graphs. DeepWalk uses local information obtained from truncated random walks to learn latent representations by treating walks as the equivalent of sentences. We demonstrate DeepWalk's latent representations on several multi label network classification tasks for social networks such as BlogCatalog, Flickr, and YouTube. Our results show that DeepWalk outperforms challenging baselines which are allowed a global view of the network, especially in the presence of missing information. DeepWalk's representations can provide F1 scores up to 10% higher than competing methods when labeled data is sparse. In some experiments, DeepWalk's representations are able to outperform all baseline methods while using 60% less training data. DeepWalk is also scalable. It is an online learning algorithm which builds useful incremental results, and is trivially parallelizable. These qualities make it suitable for a broad class of real world applications such as network classification, and anomaly detection.

title: Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
abstract: We present a new family of subgradient methods that dynamically incorporate knowledge of the geometry of the data observed in earlier iterations to perform more informative gradient based learning. Metaphorically, the adaptation allows us to find needles in haystacks in the form of very predictive but rarely seen features. Our paradigm stems from recent advances in stochastic optimization and online learning which employ proximal functions to control the gradient steps of the algorithm. We describe and analyze an apparatus for adaptively modifying the proximal function, which significantly simplifies setting a learning rate and results in regret guarantees that are provably as good as the best proximal function that can be chosen in hindsight. We give several efficient algorithms for empirical risk minimization problems with common and important regularization functions and domain constraints. We experimentally study our theoretical analysis and show that adaptive subgradient methods outperform state of the art, yet non adaptive, subgradient algorithms.

title: The Difference Between Emergency Remote Teaching and Online Learning

title: Online Learning: A Panacea in the Time of COVID 19 Crisis
abstract: Educational institutions (schools, colleges, and universities) in India are currently based only on traditional methods of learning, that is, they follow the traditional set up of face to face lectures in a classroom. Although many academic units have also started blended learning, still a lot of them are stuck with old procedures. The sudden outbreak of a deadly disease called Covid 19 caused by a Corona Virus (SARS CoV 2) shook the entire world. The World Health Organization declared it as a pandemic. This situation challenged the education system across the world and forced educators to shift to an online mode of teaching overnight. Many academic institutions that were earlier reluctant to change their traditional pedagogical approach had no option but to shift entirely to online teaching learning. The article includes the importance of online learning and Strengths, Weaknesses, Opportunities, Challenges (SWOC) analysis of e learning modes in the time of crisis. This article also put some light on the growth of EdTech Start ups during the time of pandemic and natural disasters and includes suggestions for academic institutions of how to deal with challenges associated with online learning.

title: Online learning amid the COVID 19 pandemic: Students perspectives
abstract: This research study examines the attitudes of Pakistani higher education students towards compulsory digital and distance learning university courses amid Coronavirus (COVID 19) Undergraduate and postgraduate were surveyed to find their perspectives about online education in Pakistan. The findings of the study highlighted that online learning cannot produce desired results in underdeveloped countries like Pakistan, where a vast majority of students are unable to access the internet due to technical as well as monetary issues. The lack of face to face interaction with the instructor, response time and absence of traditional classroom socialization were among some other issues highlighted by higher education students.

title: Advantages, Limitations and Recommendations for online learning during COVID 19 pandemic era
abstract: During COVID 19 pandemic, the institutions in Pakistan have started online learning. This study explores the perception of teachers and students regarding its advantages, limitations and recommendations.  This qualitative case study was conducted from March to April 2020. Using maximum variation sampling, 12 faculty members and 12 students from University College of Medicine and University College of Dentistry, Lahore were invited to participate. Four focus group interviews, two each with the faculty and students of medicine and dentistry were carried out. Data were transcribed verbatim and thematically analyzed using Atlas Ti.  The advantages included remote learning, comfort, accessibility, while the limitations involved inefficiency and difficulty in maintaining academic integrity. The recommendations were to train faculty on using online modalities and developing lesson plan with reduced cognitive load and increased interactivities.  The current study supports the use of online learning in medical and dental institutes, considering its various advantages. Online learning modalities encourage student centered learning and they are easily manageable during this lockdown situation.

title: Distance education: a systems view of online learning
abstract: Moore and Kearsley propose that a distance education system contains subsystems and is also embedded within larger systems. They begin their book by likening distance education to a human body, whi.

title: Young children's online learning during COVID 19 pandemic: Chinese parents' beliefs and attitudes
abstract: Online learning has been widely promoted to replace traditional face to face learning during the COVID 19 pandemic to maintain young children's learning and play at home. This study surveyed 3275 Chinese parents' beliefs and attitudes around young children's online learning during the lockdown of the COVID 19 pandemic. Most parents (92.7% in the study reported that their children had online learning experiences during the pandemic, and many (84.6% spent less than a half hour each time. The parents generally had negative beliefs about the values and benefits of online learning and preferred traditional learning in early childhood settings. They tended to resist and even reject online learning for three key reasons: the shortcomings of online learning, young children's inadequate self regulation, and their lack of time and professional knowledge in supporting children's online learning. Also, the hardship caused by the COVID 19 pandemic has made them suffering, thus more resistant to online learning at home. The results suggested that the implementation of online learning during the pandemic has been problematic and challenging for families. The Chinese parents were neither trained nor ready to embrace online learning. The paper concluded with implications for policymakers and teacher education.

title: Reviewing Online Learning Facing the Covid 19 Outbreak
abstract: Online learning is urgently needed to keep up with the development of the world of education which is supported by information technology that leads to the digital era both process and content in the era of the industrial revolution 4.0. With online learning, learning process can happen anywhere and anytime flexibly. Referred to as the emergence of the covid 19 outbreak that threw the world away, so it is necessary to maintain vigilance, which is through the interaction of direct contact with other humans, so that the impact on learning disrupted at school can therefore be overcome by implementing online learning. This article discusses online learning to deal with the covid 19 outbreak. The results of the study found that the need for preparation, clear steps in applying online learning, the role of the teacher, the role of the students, the benefits of online learning and overcoming the limitations of online learning.

title: EXPLORING COLLABORATIVE ONLINE LEARNING
abstract: An investigation was carried out to determine the extent to which evidence of collaborative learning could be identified in students' textual interactions in an online learning environment. The literature on collaborative learning has identified a range of behaviors that characterize successful collaborative learning in face to face situations. Evidence of these behaviors was sought in the messages that were posted by students as they interacted in online work groups. Analysis of students' contributions reveals that there is substantial evidence of collaboration, but that there are differences between conventional face to face instances of collaborative learning and what occurs in an asynchronous, networked environment.