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Post-harvest diseases of apple are one of the major issues in the economical sector of apple production, causing severe economical losses to producers. Thus, we developed DSSApple, a picture-based decision support system able to help users in the diagnosis of apple diseases. Specifically, this paper addresses the problem of sequentially optimizing for the best diagnosis, exploiting past interactions with the system and their contextual information (i.e., the evidence provided by the users), while exploring the set of candidate diseases. This online learning problem is commonly addressed in the literature through a stochastic active learning paradigm - i.e., Contextual Multi-Armed Bandit (CMAB). The methodology interactively updates the decision model considering the success of each past interaction with respect to the context provided in each round. However, contextual information is very often partial and inadequate to handle such a complex decision making problem. On the other hand, human-made decisions implicitly include unobserved factors (referred to as unobserved confounders) that significantly influence their choices. In this paper, we take advantage of the information embedded in the observed human decisions to marginalize confounders and improve the capability of the CMAB model to identify the correct diagnosis. Specifically, we propose a Counterfactual Thompson Sampling (CF-TS), a CMAB model based on the causal concept of counterfactual. The proposed model is validated with offline experiments based on data collected through a large user study on DSSApple application. The results prove that CF-TS is able to significantly outperform both traditional CMAB algorithms and observed user decisions, in the real-world task of predicting the correct apple disease.

This chapter examines the opportunities and barriers of promoting students’ learning skills, including communication, cooperation, collaboration and connection using the Wiki tool under the blackboard platform. A Wiki tool was implemented in two postgraduate units in an Australian university to develop and improve students’ professional and personal skills, i.e. communication, leadership, time management, problem-solving and decision-making. A Wiki tool becomes essential in teaching and learning, to promote students’ skills, and control their own learning and access to knowledge, cutting-edge technology and news nationally and internationally. To implement this for students in developed and developing countries, universities and the higher education sector must recognize and achieve the Millennium Development Goals (MDG) which were signed by 189 United Nation member states in September 2000, the second goal of which is related to education. This chapter provides empirical evidence, gathered through mixed methods, from 88 students who have been exposed to Wiki as a teaching tool. Student’s feedback indicates that the use of Wiki in the higher education setting is valuable and gratifying as it enables students to develop and enhance several skills, including communication, collaboration, interpersonal, writing, reading, and search/research, problem-solving and decision-making, all of which are required for both their current studies and their futures in the real-world workplace. In addition, students show their satisfaction with the Wiki’s tool, as it develops specific skills for the current study and for the future workplace, i.e. cultural awareness and cutting edge.