Artificial Intelligence (AI)-enabled remote learning and teaching using Pedagogical Conversational Agents and Learning Analytics

2021 ◽  
pp. 3-29
Author(s):  
Amara Atif ◽  
Meena Jha ◽  
Deborah Richards ◽  
Ayse A. Bilgin
Keyword(s):  
Artificial Intelligence ◽  
Learning Analytics ◽  
Conversational Agents ◽  
Learning And Teaching ◽  
Remote Learning

A fully automated conversational agent with artificial intelligence capabilities (Youper) for treating depression and anxiety: A nonrandomized feasibility trial (Preprint)

2019 ◽  
Author(s):  
Jose Hamilton Vargas ◽  
Thiago Antonio Marafon ◽  
Diego Fernando Couto ◽  
Ricardo Giglio ◽  
Marvin Yan ◽  
...  
Keyword(s):  
Mental Health ◽  
Artificial Intelligence ◽  
Financial Incentives ◽  
Empirical Support ◽  
Digital Technologies ◽  
Feasibility Trial ◽  
Depression And Anxiety ◽  
Conversational Agents ◽  
Symptoms Of Depression ◽  
Viable Solution

BACKGROUND Mental health conditions, including depression and anxiety disorders, are significant global concerns. Many people with these conditions don't get the help they need because of the high costs of medical treatment and the stigma attached to seeking help. Digital technologies represent a viable solution to these challenges. However, these technologies are often characterized by relatively low adherence and their effectiveness largely remains empirical unverified. While digital technologies may represent a viable solution for this persisting problem, they often lack empirical support for their effectiveness and are characterized by relatively low adherence. Conversational agents using artificial intelligence capabilities have the potential to offer a cost-effective, low-stigma and engaging way of getting mental health care. OBJECTIVE The objective of this study was to evaluate the feasibility, acceptability, and effectiveness of Youper, a mobile application that utilizes a conversational interface and artificial intelligence capabilities to deliver cognitive behavioral therapy-based interventions to reduce symptoms of depression and anxiety in adults. METHODS 1,012 adults with symptoms of depression and anxiety participated in a real-world setting study, entirely remotely, unguided and with no financial incentives, over an 8-week period. Participants completed digital versions of the 9-item Patient Health Questionnaire (PHQ-9) and the 7-item Generalized Anxiety Disorder scale (GAD-7) at baseline, 2, 4, and 8 weeks. RESULTS After the eight-week study period, depression (PHQ-9) scores of participants decreased by 48% while anxiety (GAD-7) scores decreased by 43%. The RCI was outside 2 standard deviations for 93.0% of the individuals in the PHQ-9 assessment and 90.7% in the GAD-7 assessment. Participants were on average 24.79 years old (SD 7.61) and 77% female. On average, participants interacted with Youper 0.9 (SD 1.56) times per week. CONCLUSIONS Results suggest that Youper is a feasible, acceptable, and effective intervention for adults with depression and anxiety. CLINICALTRIAL Since this study involved a nonclinical population, it wasn't registered in a public trials registry.

scholarly journals The institutional decisions to support remote learning and teaching during the COVID-19 pandemic

2020 ◽  
Author(s):  
Francisco Jose Garcia-Penalvo ◽  
Ricardo Rivero-Ortega Rector ◽  
Maria Jose Rodriguez-Conde ◽  
Nicolas Rodriguez-Garcia
Keyword(s):  
Learning And Teaching ◽  
Remote Learning

Learning Analytics Tool for Bulgarian School Education

2021 ◽  
Vol LXIV (4) ◽  
pp. 410-424
Author(s):  
Silvia Gaftandzhieva ◽  
◽  
Rositsa Doneva ◽  
George Pashev ◽  
Mariya Docheva ◽  
...  
Keyword(s):  
Financial Management ◽  
Learning Analytics ◽  
School Education ◽  
Accounting Systems ◽  
Learning And Teaching ◽  
Digital Repositories ◽  
Stakeholder Groups ◽  
Data Driven Decisions ◽  
Learning Data

Nowadays, schools use many information systems to automate their activities for different stakeholders’ groups – learning management systems, student diary, library systems, digital repositories, financial management and accounting systems, document processing systems, etc. The huge amount of data generated by the users of these systems, led to increased interest in the collection and analysis of data to encourage students to achieve higher results, teachers to provide personalized support and school managers to make data-driven decisions at all levels of school, and stimulates research into the application of Learning Analytics (LA) in schools. The paper presents a LA model and a software prototype of the LA tool designed for the needs of Bulgarian school education from the perspective of different stakeholder groups (students, teachers, class teachers, parents, school managers, inspectors from evaluation agencies), aiming to improve school methods of approaching and analyzing learning data. The tool allows stakeholders to track data for students’ learning or training for different purposes, e.g. monitoring, analysis, forecast, intervention, recommendations, etc., but finally to improve the quality of learning and teaching processes. Research and experiments with the model and the LA tool under consideration are conducted based on the information infrastructure of a typical Bulgarian school.

Primary Care: The Actual Intelligence Required for Artificial Intelligence to Advance Health Care and Improve Health (Preprint)

2021 ◽  
Author(s):  
Winston R. Liaw ◽  
John M Westfall ◽  
Tyler S Williamson ◽  
Yalda Jabbarpour ◽  
Andrew Bazemore
Keyword(s):  
Artificial Intelligence ◽  
Primary Care ◽  
Vital Signs ◽  
Patient Privacy ◽  
Conversational Agents ◽  
Care Needs ◽  
Remote Sensors ◽  
Delivery Platform ◽  
And Training ◽  
Improve Health

UNSTRUCTURED With conversational agents triaging symptoms, cameras aiding diagnoses, and remote sensors monitoring vital signs, the use of artificial intelligence (AI) outside of hospitals has the potential to improve health, according to a recently released report from the National Academy of Medicine. Despite this promise, AI’s success is not guaranteed, and stakeholders need to be involved with its development to ensure that the resulting tools can be easily used by clinicians, protect patient privacy, and enhance the value of the care delivered. A crucial stakeholder group missing from the conversation is primary care. As the nation’s largest delivery platform, primary care will have a powerful impact on whether AI is adopted and subsequently exacerbates health disparities. To leverage these benefits, primary care needs to serve as a medical home for AI, broaden its teams and training, and build on government initiatives and funding.

Affective Agents in E-Learning Platforms

2012 ◽  
pp. 1225-1233
Author(s):  
Christos N. Moridis ◽  
Anastasios A. Economides
Keyword(s):  
Artificial Intelligence ◽  
Learning Environments ◽  
Intelligent Agents ◽  
Intelligent Agent ◽  
Human Learning ◽  
Human Reasoning ◽  
Conversational Agents ◽  
Emotional Aspects ◽  
E Learning ◽  
Learning Platforms

During recent decades there has been an extensive progress towards several Artificial Intelligence (AI) concepts, such as that of intelligent agent. Meanwhile, it has been established that emotions play a crucial role concerning human reasoning and learning. Thus, developing an intelligent agent able to recognize and express emotions has been considered an enormous challenge for AI researchers. Embedding a computational model of emotions in intelligent agents can be beneficial in a variety of domains, including e-learning applications. However, until recently emotional aspects of human learning were not taken into account when designing e-learning platforms. Various issues arise when considering the development of affective agents in e-learning environments, such as issues relating to agents’ appearance, as well as ways for those agents to recognize learners’ emotions and express emotional support. Embodied conversational agents (ECAs) with empathetic behaviour have been suggested to be one effective way for those agents to provide emotional feedback to learners’ emotions. There has been some valuable research towards this direction, but a lot of work still needs to be done to advance scientific knowledge.

Opportunities and Challenges of Adopting Artificial Intelligence for Learning and Teaching in Higher Education

2021 ◽  
pp. 67-78
Author(s):  
Aniekan Essien ◽  
Godwin Chukwukelu ◽  
Victor Essien
Keyword(s):  
Artificial Intelligence ◽  
Higher Education ◽  
Emerging Technologies ◽  
Higher Education Institutions ◽  
Practical Applications ◽  
Learning And Teaching ◽  
Teaching In Higher Education

This chapter provides a sense of what artificial intelligence is, its benefits, and integration to higher education. Seeing through the lens of the literature, this chapter will also explore the emergence of artificial intelligence and its attendant use for learning and teaching in higher education institutions. It begins with an overview of artificial intelligence and proceeds to discuss practical applications of emerging technologies and artificial intelligence on the manner in which students learn as well as how higher education institutions teach and develop. The chapter concludes with a discussion on the challenges of artificial intelligence on higher education.

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