In the 2010/11 academic year, more than one fifth of international students in the American higher education institutions were from Mainland China. However, these Chinese students were often addressed by American professors as "passive listeners" or "inactive learners": they were quiet in the classroom and seldom asked question. In this paper, the investigator examined five Chinese graduate students in an American university on their experiences and perceptions on asking question in the American classrooms. A qualitative multiple case study was conducted with individual face-to-face interview as the major data collection instrument. The two research questions are: 1) What are the experiences of Chinese international students about asking questions in graduate level classes in the United States? 2) How do Chinese international graduate students feel about asking questions in the American classroom? It was found that the major issues influenced the participants' question-asking behavior were: 1) English deficiency, 2) cultural differences between China and America, and 3) the different educational environment between these two countries. Specifically, the participants' motivation and opportunity to ask question in the classroom was influenced by their belief that teacher should be respected, the value of question, and the Chinese concepts of thinking and speaking. The classroom environment in terms of the classroom behavior of American professors and other students also had impacts on the participants' question-asking behavior as an external contextual factor. Based on the findings of this study, recommendations were offered for American faculty members and staffs working with international students and incoming Chinese students. This study might help American professors better understand the unique learning styles of their Chinese students and inform institution administrators to improve the services for international students. The results may also help Chinese students adapt to the American educational community smoothly. Suggestions for further study were also provided for researchers who were interested to increase international/ Chinese students' classroom participation.

In many ways, higher educational systems in the United States are the most extraordinary in the world. Students come from all over to study in our institutes of higher learning. As our search for an explanation of how to facilitate student learning continues, the goal of this dissertation was to examine the heavily under-researched area of teacherstudent relationships as they relate to student understanding. Using the existing body of instructional communication research, the Student Understanding Model (SUM) is proposed and tested. Data collected from 302 undergraduate students was used to test the SUM. Results provide empirical support that relational messages account for approximately 26% of the variance in student understanding. Conclusions and implications from the current study were discussed.

Question-asking has long been an integral part of human learning. In scholarly investigations over the past several decades, questions have been studied in terms of the answers they generate, their grammatical structure, their cognitive functions, their logical content, and their social dynamics. Studies of student classroom questioning have focused on science education and reading instruction particularly; they detail the reasons why students don't ask questions and explore a plethora of recommendations about teaching students how to question. This qualitative study addressed question-asking from a hermeneutic moral realist perspective, studying question-asking as it unfolded in the everyday practice of learning in a graduate seminar on design thinking. Findings of the study included seven themes that fit within three broader metathemes about the complexities and virtues of classroom questioning, the sociality of question-asking, and the temporality of questions in practice. Specific themes of the study concerned the complexity of overlapping practices within the classroom, ways in which students evaluated the quality and virtue of their questioning interactions, the moral reference points that guided student participation in various kinds of questioning (i.e., convergent questions, divergent questions, challenges to others), and the temporality of question-asking that reflected the way questions mattered to the students and how different aspects of the subject matter were disclosed and concealed in the process of learning. Findings from this study suggest that a moral realist-oriented inquiry can provide a wide-ranging and nuanced set of insights regarding question-asking as a part of student learning.

Intelligent Tutoring Systems (ITSs) are problem-solving environments that provide individualised instruction and are able to adapt to the abilities and needs of each individual student in order to maximise effective learning. They provide feedback on students' actions, but a problem arises when students do not always understand the feedback they receive. Therefore, it would be beneficial for students to be able to ask for additional clarifications at any time, and to receive feedback customised to their individual differences. This research focuses on providing an additional help channel in ITSs where students are able to ask free-form questions, as well as accounting for the students' psychometric measure of spatial ability. We describe ERM-Tutor, the test-bed ITS chosen for implementing our research framework. ERM-Tutor is a constraint-based tutoring system for teaching logical database design. Students practise this procedural task in ERM-Tutor by solving each step and receiving feedback on their solutions. We also present our approach to addressing the meta-cognitive skill of question-asking in ERM-Tutor. We added a question-asking module that enables students to ask free-form questions and receive the most appropriate answers stored in the system. In addition, we investigated the potential of tailoring the feedback messages towards the learners' psychometric measure of spatial ability. We modified ERM-Tutor to provide not only textual feedback messages, but also multimedia messages, containing a combination of text and pictures. We performed a series of evaluation studies in order to evaluate the effectiveness of our proposed solutions. All our studies were conducted with tertiary students enrolled in an introductory database course. The students had attended lectures on logical database design and were asked to use ERM-Tutor to develop and practise their mapping skills. The results show an overall improvement in performance and learning gain for all students using ERM-Tutor. Interactions with the question-asking module show that most questions asked by students were task-focused, directly requesting help on specific errors. The results confirm the need for addressing students' questions inside an ITS environment. Furthermore, there were no conclusive results to support a difference in effectiveness of the textual versus multimedia feedback presentation modes with respect to the students' spatial ability. However, we observed a number of trends indicating that matching the instruction presentation mode towards the students spatial ability influences their perception of the system and motivation to use it, more than their learning gain. Our results show promising indications for further explorations. We present our approaches, full analyses of the collected data from our evaluation studies, as well as our research contributions to the ITSs field. We also portray a number of future directions that will contribute towards maximising the effectiveness of learning in ITSs.

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Intelligent tutoring systems (ITSs) are computer programs that model individual learners and adapt instruction to help each learner differently. One way ITSs differ from human tutors is that few ITSs give learners a way to ask questions. When learners can ask for help, their questions have the potential to improve learning directly and also act as a new source of model data to help the ITS personalize instruction. Inquiry modeling gives ITSs the ability to answer learner questions and refine their learner models with an inexpensive new input channel. In order to support inquiry modeling, an advanced planning formalism is applied to ITS learner modeling. Partially observable Markov decision processes (POMDPs) differ from more widely used ITS architectures because they can plan complex action sequences in uncertain situations with machine learning. Tractability issues have previously precluded POMDP use in ITS models. This dissertation introduces two improvements, priority queues and observation chains, to make POMDPs scale well and encompass the large problem sizes that real-world ITSs must confront. A new ITS was created to support trainees practicing a military task in a virtual environment. The development of the Inquiry Modeling POMDP Adaptive Trainer (IMP) began with multiple formative studies on human and simulated learners that explored inquiry modeling and POMDPs in intelligent tutoring. The studies suggest the new POMDP representations will be effective in ITS domains having certain common characteristics. iv Finally, a summative study evaluated IMP’s ability to train volunteers in specific practice scenarios. IMP users achieved post-training scores averaging up to 4.5 times higher than users who practiced without support and up to twice as high as trainees who used an ablated version of IMP with no inquiry modeling. IMP’s implementation and evaluation helped explore questions about how inquiry modeling and POMDP ITSs work, while empirically demonstrating their efficacy