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The MOOC pivot
What happened to disruptive transformation of education? When massive open online courses (MOOCs) first captured global attention in 2012, advocates imagined a disruptive transformation in postsecondary education. Video lectures from the world's best professors could be broadcast to the farthest reaches of the networked world, and students could demonstrate proficiency using innovative computer-graded assessments, even in places with limited access to traditional education. But after promising a reordering of higher education, we see the field instead coalescing around a different, much older business model: helping universities outsource their online master's degrees for professionals ( 1 ). To better understand the reasons for this shift, we highlight three patterns emerging from data on MOOCs provided by Harvard University and Massachusetts Institute of Technology (MIT) via the edX platform: The vast majority of MOOC learners never return after their first year, the growth in MOOC participation has been concentrated almost entirely in the world's most affluent countries, and the bane of MOOCs—low completion rates ( 2 )—has not improved over 6 years.
Journal Article
Cai Guo-Qiang
\"A discussion of the art, materials, and techniques of contemporary Chinese artist Cai Guo-Qiang, well known for his subversive use of materials, especially his signature material, gunpowder\"-- Provided by publisher.
BOOK
Artificial Intelligence for Assessment and Feedback to Enhance Student Success in Higher Education
The core focus of this review is to show how immediate and valid feedback, qualitative assessment influence enhances students learning in a higher education environment. With the rising trend of online education especially in this COVID-19 pandemic, the role of assessment and feedback also changes. Earlier the assessment part is not considered the main focus in learning and teaching in HEIs, but now with the increase in online education, it is observed that the paradigm is shifted toward assessing those activities of students that enhance their learning outcomes. A lot of research work has been done on developing assessment strategies and techniques that can support learning and teaching effectively. Yet, there is limited research that looks at how methods applied in learning analytics can be used and possibly constitutes the assessment process. The objective of this work is to provide an exploratory and comparative study of how assessment and feedback practices can enhance students learning outcomes using AI. The key contribution of this study attempts to capture an outline of the most used artificial intelligence and machine learning algorithms for student success. The results showed that I-FCN performed better than other techniques (ANN, XG Boost, SVM, Random Forest, and Decision Trees) in all measured performance metrics. Also, the result of the comparative analysis study will help the educators, instructors, and administrators on how they could take the advantage of a data-driven approach, design less pressurized, more valid, reliable, constructive assessment findings, and connect the power of assessment and feedback to enhance the learning outcomes.
Journal Article
A survey on missing data in machine learning
Machine learning has been the corner stone in analysing and extracting information from data and often a problem of missing values is encountered. Missing values occur because of various factors like missing completely at random, missing at random or missing not at random. All these may result from system malfunction during data collection or human error during data pre-processing. Nevertheless, it is important to deal with missing values before analysing data since ignoring or omitting missing values may result in biased or misinformed analysis. In literature there have been several proposals for handling missing values. In this paper, we aggregate some of the literature on missing data particularly focusing on machine learning techniques. We also give insight on how the machine learning approaches work by highlighting the key features of missing values imputation techniques, how they perform, their limitations and the kind of data they are most suitable for. We propose and evaluate two methods, the k nearest neighbor and an iterative imputation method (missForest) based on the random forest algorithm. Evaluation is performed on the Iris and novel power plant fan data with induced missing values at missingness rate of 5% to 20%. We show that both missForest and the k nearest neighbor can successfully handle missing values and offer some possible future research direction.
Journal Article
The boy from Clearwater. Book 2
\"After his imprisonment in Green Island, Kun-lin struggles to pick up where he left off ten years earlier. He reconnects with his childhood crush Kimiko and finds work as an editor, jumping from publisher to publisher until finally settling at an advertising company. But when manhua publishing becomes victim to censorship, and many of his friends lose their jobs, Kun-lin takes matters into his own hands. He starts a children's magazine, Prince, for a group of unemployed artists and his old inmates who cannot find work anywhere else. Kun-lin's life finally seems to be looking up... but how long will this last? Forty years later, Kun-lin serves as a volunteer at the White Terror Memorial Park, promoting human rights education. There, he meets Yu Pei-yun, a young college professor who provides him with an opportunity to reminisce on his past and how he picked himself up after grappling with bankruptcy and depression. With the end of martial law, Kun-lin and other former New-Lifers felt compelled to mobilize to rehabilitate fellow White Terror victims, forcing him to face his past head-on. While navigating his changing homeland, he must conciliate all parts of himself--the victim and the savior, the patriot and the rebel, a father to the future generation and a son to the old Taiwan--before he can bury the ghosts of his past.\"--Amazon.com.
BOOK
Students under lockdown: Comparisons of students’ social networks and mental health before and during the COVID-19 crisis in Switzerland
This study investigates students' social networks and mental health before and at the time of the COVID-19 pandemic in April 2020, using longitudinal data collected since 2018. We analyze change on multiple dimensions of social networks (interaction, friendship, social support, co-studying) and mental health indicators (depression, anxiety, stress, loneliness) within two cohorts of Swiss undergraduate students experiencing the crisis (N = 212), and make additional comparisons to an earlier cohort which did not experience the crisis (N = 54). In within-person comparisons we find that interaction and co-studying networks had become sparser, and more students were studying alone. Furthermore, students' levels of stress, anxiety, loneliness, and depressive symptoms got worse, compared to measures before the crisis. Stressors shifted from fears of missing out on social life to worries about health, family, friends, and their future. Exploratory analyses suggest that COVID-19 specific worries, isolation in social networks, lack of interaction and emotional support, and physical isolation were associated with negative mental health trajectories. Female students appeared to have worse mental health trajectories when controlling for different levels of social integration and COVID-19 related stressors. As universities and researchers discuss future strategies on how to combine on-site teaching with online courses, our results indicate the importance of considering social contacts in students' mental health and offer starting points to identify and support students at higher risk of social isolation and negative psychological effects during the COVID-19 pandemic.
Journal Article
The boy from Clearwater. Book 1
\"An incredible true story in graphic novel form that lays bare the tortured and triumphant history of Taiwan, an island claimed and fought over by many countries, through the life story of a man who lived through its most turbulent times\"-- Provided by publisher.
BOOK
Coronavirus pushes education online
Litao Sun, Yongming Tang and Wei Zuo reflect on their experience of nationwide distance learning in China’s universities during the COVID-19 outbreak.
Journal Article