Recommendation of Learning Resources based on Social Relations

Putri Ajusti Zalmi (19016186) Esai Metlit Bahasa Inggris

10.31219/osf.io/snzyt ◽

2021 ◽

Author(s):

Putri Ajusti Zalmi

Keyword(s):

Learning Environment ◽

Language Learning ◽

Social Relations ◽

Learning Process ◽

Learning Resources

The environment has an influence on a person, especially in the use of language. Language is a means of communication acquired by humans from birth. The use of language is closely related to social relations between speakers in the midst of language learning. The learning process is a process of interaction between students and learning resources in a learning environment.

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The Relationsip of Indonesian Learning With Enivornment

10.31219/osf.io/v2cw9 ◽

2021 ◽

Author(s):

Nurul Aliyah

Keyword(s):

Learning Environment ◽

Language Learning ◽

Social Relations ◽

Learning Process ◽

Learning Resources

The environment has an influence on a person, especially in the use of language. Language is a means of communication acquired by humans from birth. The use of language is closely related to social relations between speakers in the midst of language learning. The learning process is a process of interaction between students and learning resources in a learning environment.

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Dental students' choice of learning resources

Journal of Dental Education ◽

10.1002/j.0022-0337.1995.59.11.tb02989.x ◽

1995 ◽

Vol 59 (11) ◽

pp. 1055-1057

Author(s):

AL Fairclough ◽

PV Carrotte

Keyword(s):

Dental Students ◽

Learning Resources

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The SRM Approach to Family Assessment

European Journal of Psychological Assessment ◽

10.1027/1015-5759.21.4.216 ◽

2005 ◽

Vol 21 (4) ◽

pp. 216-225 ◽

Cited By ~ 21

Author(s):

William L. Cook

Keyword(s):

High Risk ◽

Risk Behaviors ◽

Social Relations ◽

Family Relationships ◽

Family Dynamics ◽

Family Assessment ◽

High Risk Behaviors ◽

Analysis Group ◽

The Social ◽

Direction Of Effects

Abstract. In family systems, it is possible for one to put oneself at risk by eliciting aversive, high-risk behaviors from others ( Cook, Kenny, & Goldstein, 1991 ). Consequently, it is desirable that family assessments should clarify the direction of effects when evaluating family dynamics. In this paper a new method of family assessment will be presented that identifies bidirectional influence processes in family relationships. Based on the Social Relations Model (SRM: Kenny & La Voie, 1984 ), the SRM Family Assessment provides information about the give and take of family dynamics at three levels of analysis: group, individual, and dyad. The method will be briefly illustrated by the assessment of a family from the PIER Program, a randomized clinical trial of an intervention to prevent the onset of psychosis in high-risk young people.

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Meta-Accuracy and Perceived Reciprocity From the Perception-Meta-Perception Social Relations Model

Social Psychology ◽

10.1027/1864-9335/a000356 ◽

2019 ◽

Vol 50 (1) ◽

pp. 24-37

Author(s):

Ben Porter ◽

Camilla S. Øverup ◽

Julie A. Brunson ◽

Paras D. Mehta

Keyword(s):

Structural Equation Modeling ◽

Social Relations ◽

Latent Variables ◽

Structural Equation ◽

Multilevel Structural Equation Modeling ◽

Equation Modeling ◽

Complete Understanding ◽

Social Relations Model ◽

Flexible Framework ◽

Multilevel Structural Equation

Abstract. Meta-accuracy and perceptions of reciprocity can be measured by covariances between latent variables in two social relations models examining perception and meta-perception. We propose a single unified model called the Perception-Meta-Perception Social Relations Model (PM-SRM). This model simultaneously estimates all possible parameters to provide a more complete understanding of the relationships between perception and meta-perception. We describe the components of the PM-SRM and present two pedagogical examples with code, openly available on https://osf.io/4ag5m . Using a new package in R (xxM), we estimated the model using multilevel structural equation modeling which provides an approachable and flexible framework for evaluating the PM-SRM. Further, we discuss possible expansions to the PM-SRM which can explore novel and exciting hypotheses.

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