Human Information Interaction

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Background and Aim: Information literacy is a contextual concept that needs to be studied in different contexts like schools. Promoting reading literacy is a core instructional objectives of Persian literature curriculum and also a part of information literacy. Understanding Concept of information literacy helps us to understand information literacy in elementary schools and can implement it in information literacy Instruction and Assessment of schools.

Methods: This research is a phenomenological research that used Qualitative Content Analysis technique for analyzing Semi structured interviews and Observations. Theoretical sampling was used and three schools were selected. We interview with four Teachers and observed four classes in Fourth Grade.

Findings: based on data analyzing we can describe information literacy for language in  Fourth Grade in this phrases: “Set the scene: Make a space for thinking, reflecting and planning”, “ emerging of determining information need”, “locating and searching of information”, “information engagement”, “information Processing”, “record, organize and ethical use of information”, “Communication”, “Presentation”.

Result: based on findings, teachers highly focused on developing skills of information engagement(reading, listening, viewing), Information Processing(supplying Infrastructures of text understandings; Practice textual, audio, visual comprehension; practicing information processing in action), presenting information(in written and Unwritten format and learning how to do them). Integrating information literacy with language curriculum seems that can help to achieve language instructional objectives. The findings can be used for designing instrument of information literacy assessment and also can be used for teacher training.

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Background and Aim: Due to recent attention to health promotion and self-care as one of the prerequisites of health services and intervention programs, health information seeking behavior research has gain increasing importance. Factors such as attention to user centered studies, context and self-care require using of methods and tools that help study people in their natural environment. However, review studies have shown the dominance of quantitative and positivist approaches in health information seeking behavior studies. This study aims at introducing episodic interview as a tool for gathering unique data from peoples’ natural lives and its application in health information seeking studies.
Method: This review article has been conducted by library method. It addresses health information seeking behavior concept and its affecting factors. It also introduces episodic interview and its underlying concepts including narration and narrative interviewing. Further, it investigates implications of applying episodic interview in health information behavior studies and eventually it discusses steps of conducting episodic interview with examples of narrations.
Findings: The strength point of episodic interview is its focus on narration of people about their lived experiences as research data which help researchers study and analyze people in a different way from conventional approaches. Implications of applying episodic interview are: 1.concentration of health information behavior studies on pattern of behavior, 2. health information seeking behavior being interwoven in everyday life, and 3. health information seeking behavior being intentional and purposeful.
Results: Episodic interview help researchers listen to the voices of different groups of people, especially whom their voice is not heard due to sickness and social and cultural conditions, a point which should be considered in designing any information and intervention services. 

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Background and Aim: The meaning of cross-domain recommendation is that instead of dealing with each domain independently, transfer knowledge gained in one domain (source) to another domain (target) and use it. The present article systematically reviews the research in this field in terms of foundations, applications and challenges.
Method: The Prisma guidelines had been used. Search in Persian and English scientific information sources with related keywords were conducted and 98 English language sources were found in the period 2007 to 2021. Applying the initial refinement, inclusion and exclusion criteria by experts, 28 English documents were selected to enter in the systematic review.
Findings: There are four levels of cross-domain recommendations: Attributes, types, items and systems. Machine learning algorithms are used to predict user rating in cross-domain recommendations, and three categories of:  Prediction, ranking, and classification criteria are used to evaluate predictions based on confusion matrix. Cross-domain recommendations can be used to increase the accuracy of recommendations, resolve cold start problems, cross-sell, and improve personalization by transferring knowledge between domains. The most challengeable recommendations of cross-domain is the differences between domains. These differences include the mismatch between the properties of the domains and/or unclear relationships between the domains. In addition, differences in domain size and poor performance of basic algorithms in predicting user rating are other challenges in cross-domain recommendations.
Conclusion: While this subject has been shaped in the last decade, but the keen attention of computer science and information researchers shows its importance. Items level are the main category of cross-domain recommendations. Due to the formation of e-business groups, in the future, cross-domain recommendations at the system level will be given more consideration. Cross-domain recommendations could be used to improve the performance of recommender systems, user modeling in human-computer interaction, and e-commerce.