Effectiveness of Storybased Visual and Agile Teaching Method for Nontechnical Adult Learners Who Want to Understand Artificial Intelligence This study proposes and evaluates an effective teaching method for nontechnical adults who want to understand artificial intelligence (AI). As the number of nontechnical business professionals who want to improve their participation in technical discussions is increasing, it becomes important to find effective teaching methods for nontechnical adults who need to understand core technical concepts in which they are involved reasonably. The proposed teaching method utilizes the active use of visual feedback and agile practices to overcome the challenges the adult learners face. In this study, we evaluated the effectiveness of the proposed teaching method by the open coding method to analyze the freeform responses and by the paired ttest over the responses to the questions asked to the participants before and after the lecture. We found that this teaching method effectively supported the learners to understand the basic technical concepts of AI within one or twoday time frame. We also confirmed the nontechnical adult learners had significantly changed their attitude toward understanding AI from initially negative to positive with a good expectation of success in understanding AI, which is one of the important outcomes for the learners as the expectancyvalue theory predicts their future performance on understanding AI.

Investigating Soft Skills Development through Peer Reviews Assessments in an Entrepreneurship Course In this paper we present an approach to stimulate the development of soft skills in tertiary education students, which are seen as critical skills for active citizenship, personal fulfillment and employability in a knowledgedriven society. We developed an online learning setting where technical graduate students practice and gain knowledge on Innovation and Entrepreneurship themes. We present the early results of a peer assessment exercise where students submit assignments and evaluate other assignments made by their colleagues. We employ textual similarity measures and other effort related metrics to understand different learner types emerging in the exercise. Our results foster future directions of research on how soft skills can be studied in online environments. This study contributes to the ongoing debate on how to understand and visualize data coming from online courses and how to further the studentsxe2x80x99 assessment of soft skills development.