scholarly journals CLaDS: a cloud-based virtual lab for the delivery of scalable hands-on assignments for practical data science education

2018 ◽  
Author(s):  
Chase Geigle ◽  
Ismini Lourentzou ◽  
Hari Sundaram ◽  
ChengXiang Zhai
Keyword(s):  
Science Education ◽  
Data Science ◽  
Virtual Lab ◽  
Hands On

scholarly journals An Artificial Intelligence Tool for Accessible Science Education

2021 ◽  
Vol 24 (1) ◽  
pp. 1-14
Author(s):  
Jacob D. Watters ◽  
◽  
April Hill ◽  
Melissa Weinrich ◽  
Cary Supalo ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Science Education ◽  
Modern Science ◽  
Laboratory Work ◽  
Raspberry Pi ◽  
Virtual Lab ◽  
Full Participation ◽  
Hands On ◽  
Voice Control ◽  
Amazon Web Services

One of the most important issues in accessible science education is creating a laboratory workspace accessible to blind students or students with visual impairments (VI). Although these students are often provided access to the science lectures, they are usually denied full participation in hands-on laboratory work. Current solutions to this problem focus on providing special accommodations such as asking sighted lab partners to complete the hands-on work. Although the accessibility of laboratory devices in modern science education has been improved in recent years, students with VI often remain passive learners. In this work, we developed a new artificial intelligence tool, the MSU Denver Virtual Lab Assistant (VLA), using Amazon Web Services (AWS), Amazon Alexa Skills Kit (ASK), Alexa smart speaker, and a microcontroller (Raspberry Pi). The VLA can be used as a virtual assistant in the lab in combination with other access technologies and devices. The VLA allows students with VI to perform the hands-on laboratory work by themselves simply using voice control. The VLA can be accessed through any smartphone or Amazon Echo device to assist general science lab procedures. The VLA is designed to be applicable to different science laboratory work. It is also compatible with other common accessible electronic devices such as the Talking LabQuest (TLQ). We believe that the VLA can promote the inclusion of learners with VI and be beneficial to general accessible science education work.

scholarly journals Choices of pre-service science teachers laboratory environments: Hands-on or hands-off?

2018 ◽  
Vol 10 (1) ◽  
pp. 41-51
Author(s):  
Hasan Ozgur Kapici ◽  
Hasan Akçay
Keyword(s):  
Science Teachers ◽  
Conceptual Understanding ◽  
Scientific Reasoning ◽  
Service Science ◽  
Attractive Alternative ◽  
Science And Technology Education ◽  
Virtual Lab ◽  
Online Laboratory ◽  
Hands On ◽  
Scientific Reasoning Skills

AbstractLearning in laboratories for students is not only crucial for conceptual understanding, but also contributes to gaining scientific reasoning skills. Following fast developments in technology, online laboratory environments have been improved considerably and nowadays form an attractive alternative for hands-on laboratories. The study was done in order to reveal pre-service science teachers’ preferences for hands-on or online laboratory environments. Participants of the study were 41 pre-service science teachers who were enrolled in a 13-week course on laboratory applications in science education. Findings showed that more than half of the pre-service science teachers would prefer to use hands-on laboratory environments for both conceptual teaching in their classrooms and to develop their students’ science process skills. The reasons behind their choices are discussed.Keywords: Online lab, hands-on lab, virtual lab, science and technology education, pre-service science teachers.* ADDRESS FOR CORRESPONDENCE: Hasan Özgur Kapıcı , Yıldız Teknik Ünivesitesi, Istanbul, TurkeyE-mail

Integrating Big Data Services Into an Undergraduate MIS Curriculum

2017 ◽  
Vol 7 (2) ◽  
pp. 58-73 ◽  
Author(s):  
Scott Jensen
Keyword(s):  
Big Data ◽  
Real World ◽  
Data Science ◽  
Graduate Programs ◽  
Advanced Degree ◽  
Data Services ◽  
Hands On ◽  
Data Problem

There is an insatiable demand in industry for data scientists, and graduate programs and certificates are gearing up to meet this demand. However, there is agreement in the industry that 80% of a data scientist's work consists of the transformation and profiling aspects of wrangling Big Data; work that may not require an advanced degree. In this paper, the authors present hands-on exercises to introduce Big Data to undergraduate MIS students using the CoNVO Framework and Big Data tools to scope a data problem and then wrangle the data to answer questions using a real-world dataset. This can provide undergraduates with a single course introduction to an important aspect of data science.

Sign in / Sign up

Export Citation Format

Share Document