Revista Argentina de Clínica Psicológica 2020, Vol. XXIX, N°2, 193-199
DOI: 10.24205/03276716.2020.223 193
P
SYCHOANALYSIS ON
H
UMAN
-C
OMPUTER
I
NTERACTION IN
C
OLLEGE
E
DUCATION
Shan Kong
Abstract
With the advent of computer and Internet technologies, human-computer interaction has been widely adopted in online education platforms. However, there is not yet a thorough analysis on how human-computer interaction affect the psychology of students and the teaching efficiency. This paper attempts to identify the psychological response of students to the education mode involving human-computer interaction. Specifically, a psychological hierarchy model was established, with interactive behavior, psychological reflection and sensory experience as principal elements. Then, a questionnaire survey was conducted in Renmin University of China. The survey data were analyzed on the SPSS, with interface design, interactive operation, system functions, and learning content as independent variables and psychological cognition and sensual experience as dependent variables. The results show a friendly interactive design of human-computer interaction can promote the sensory and emotional experience of students, arouse their interests in learning and improve the teaching effect. The research results provide new insights into the application of human-computer interaction in college education.
Key words: human-Computer Interaction, Psychological Hierarchy Model, Questionnaire Survey, Teaching Efficiency.
Received: 18-03-19 | Accepted: 02-11-19
INTRODUCTION
With the surge of computer and Internet technologies, the online education platform has infiltrated into all walks of life, especially the education domain. We have made great strides
towards the human-computer interaction
technology from the traditional face-to-face teaching model (Mwiya, Siachinji, Bwalya et al., 2019). As a new education philosophy and model, this practice not only responds to low resource utilization but also can weaken the restriction of temporal and geographical factors. However, what most of online education systems render is the function concept and experience as viewed from engineering, but lose sight of psychological factors of students, that is,
School of Foreign Studies, Yiwu Industrial & Commercial College, Yiwu 322000, China.
E-Mail: [email protected]
they have fully ignored students’ psychological
effects such as user experience, affectional exchange and sensory judgement in the human-computer interaction mode. As a result, it is more significant to have an insight into psychological effects of students for improving the teaching efficiency in the human-computer interaction mode from the perspective of psychoanalysis.
Today, the mainstream development idea in the world is to use the human-computer interaction technology to develop and apply the E-education platform that integrates graphic art, cognitive science, human-computer interaction, interface design, etc., and build a user psychology experience model based on the principle of enhancing the user experience (Rahbari, Dehestani, & Baharlouei, 2019). However, in doing so, the concept of engineering construction is still underlying for development. There is the lack of personalized interaction design and little exchange of emotion on the education
SHAN KONG
194
platform, the low satisfaction with individualized demands of students in the whole online education platform, so that the psychological factors of students cannot be fully considered while effectively improving teaching efficiency. Therefore, based on the online human-computer interaction education model constructed based on the engineering concept, how to improve the teaching efficiency from psychology perspective has become a hot topic in academic circles.
Aim at these matters, the paper builds a psychological hierarchy model with the interactive behavior, psychological response and sensory experience as primary elements after practically making psychoanalysis of attention, memory and emotion of students based on the Web-based human-computer interaction technology. In the end, questionnaire survey is designed to qualitatively analyze students' psychological factors with the independent and dependent variables. The SPSS
software analyzes data according to the
questionnaire survey. The results show that the friendly interaction platform designed has a significant effect on students' mental feelings, and plays a positive psychological effect on students, whether in improving the sensory and emotional experience and teaching efficiency or in stimulating
the students’ interests in learning.
INFLUENCE OF HUMAN-COMPUTER
INTERACTION ON PSYCHOLOGY
Influence on attention
Attention is a syndrome of responses to a series of psychological activities such as the sense of touch, memory, cognition and feeling. In daily study and life, people only have an eye on what they care about selectively, and automatically filter out other unrelated things. Studies show that people usually fix their attention heavily on moving things, noise, human face and food. This conditional physiology response also provides a good idea for interactive design. In the human-computer interaction teaching system, sensorial stimuli, such as animation, sound, etc., may be applied for the knowledge points to which special attention should be paid. It is helpful for guiding students to recall clear teaching points with finite attention (Stevenson, Schilhab, & Bentsen, 2018).
Influence on memory
Memory is the most immediate performance of psychological activities. Based upon the distinction between short-lived and lasting memories, it is
possible to judge the information assimilation types (Rafie, Sheibani, Shahbazi et al., 2019). In the design of current teaching system, interactive interface design should be highly consistent with the option of operations. In practice, it is more significant for students to produce good memory rather than lose core learning content. Therefore, in the design of the interactive education system, the wide and narrow navigation structure will lead a better effect than the narrow and deep hierarchy type, especially in the classic version of hierarchical structure embedded with program window, dialog box and menu, students will recognize and accept it more easily since it can help students have short-lived and lasting memories. The habitual interface operation can save a lot of time and energy costs for operation-oriented actions, and is more helpful to accomplish the core and the goal as stressed in the teaching system (Zhang, Qiao, Che et al., 2019).
Influence on emotion
Emotion is not only an extremely complex cognition in the psychology realm, but also a syndrome of subjective experience, physical change, external expression and physiological change. It has a strong uncertainty and suddenness (Rutter, Scheuer, Vahia et al., 2019). Good emotions can respond to active and subjective learning attitudes, and also play a key part in the design of interactive teaching system. A good system design can give students a pleasant mood while helping improve learning efficiency. Although this subtle influence cannot be directly responded to quantitative statistics and qualitative analysis, it can be proved from the details of the students' expressions, behaviors, etc. (Mckee, Duprey, & O’Neal, 2019). Therefore, the interactive education system should fully allow for students' emotional needs and attain the functional objectives. For this purpose, we should carry out personalized design for such education system from the psychology perspective.
ESTABLISHMENT OF PSYCHOLOGICAL
HIERARCHY MODEL
Student experience element model
The student experience elements are aimed to make analytical hierarchy process in the interactive Web-based learning environment. According to the concept from concrete to abstract, and following the idea from conceptual design to objective accomplishment, it is divided into five layers, i.e. the presentation, visual, structural, scope and strategic layers (Kwag & Ju, 2019), which constitutes a model
PSYCHOANALYSIS ON HUMAN-COMPUTER INTERACTION IN COLLEGE EDUCATION 195
map for the student experience elements. The specific model diagram is shown in Figure 1. As shown in Figure 1, the interface, navigation and information in the visual layer are designed in parallel. The former has a personalized interaction
based on the students’ psychological elements, and
the latter attains the functional design based on the engineering construction. They are fully integrated from engineering and psychological perspectives to re-conceive the design of the visual layer.
Figure 1
.
Model Diagram of Students'
Experience Elements
In the design of the scope layer, the functional specifications and content requirements are juxtaposed, and the psychological factors are considered in the design of the online education environment. While accomplishing the functional learning tasks and objectives, it is enhanced with the habitual operations, the friendly interface, the importance tips and other supportive psychological cues.
Psychological hierarchy model
According to the stratification and psychology characteristics of the student experience element model, the presentation, visual, structural, scope and strategical layers in this model are re-constructed to form a structural model with three principal elements, i.e. interactive behavior, psychological reflection and sensory experience (Sharpe, Stalnaker, Schuck et al., 2019). While finishing the functional online education tasks, the focus of analysis is put on the students' inner feeling, behavioral experience and inner reflection. Then, personalized and friendly functions are designed in terms of the interface, operation and content, aiming at enhancing the development and analysis of student psychology, provided that the teaching efficiency can be improved. As shown in Figure 2, the psychological hierarchy model is built with the interactive behavior, psychological reflection and sensory experience as principal elements.
Figure 2
.
Hierarchical Model Diagram of Psychology
Visual design
Information design Navigation
design
Interaction design
Interface design
Functional specification
Information architecture
Internal demand
User demand
Website target
Pres enta
tion laye
r
Vis ual
laye r
Stru ctur
al
laye r
Scop e
laye r
Stra tegi
c
leve l Specific
Abstract
Complete
Concept
Psychological Reflective Level
Interactive Behavior Layer
Instinctive sensory layer
Thinking reaction layer
Behavioral Experience Layer
Inner Feeling Layer
Emotional experience Operation experience Functional experience Content experience
Operation experience Functional experience Content experience
Emotional Design
Interface design Interaction design Architecture Design
Functional design
Learner Feelings Learner experience Design level
Ease of use
Usability Pleasure of use
SHAN KONG
196
DESIGN OF SURVEY QUESTIONNAIRES
As required by the established psychological hierarchy model, the single choice questions are adopted in the design of the questionnaire to conduct a centralized survey. All questions follow a 5-point system for quantization. Different scores represent different meanings: 5-point represents Completely agreed; 4-point does Basically agreed; 3-point is Not sure; 2-3-point is Not quite agreed; 1-3-point is Disagreed. The testees respond directly to these questions according to actual conditions. The purpose of the questionnaire design is to
meticulously analyze how the students’ sensual
experience and psychology are subjected to the interface design, interactive operation and system learning content in the online education environment (Berthelsen, Hakanen, & Westerlund, 2018).
The survey questionnaire can be designed with the interface in the instinctive sensory layer and the interactive operation, learning content and system functions in the interactive behavior layer as
independent variables, and the emotional
experience in the psychological reflection layer and the interface experience, visual and browsing experience in the instinctive sensory layer as dependent variables (Printza, Kalaitzi, Bakirtzis et al., 2018).
Design of independent variables
The design of the independent variables defines and decomposes multiple indicators such as the interface design, interactive operation, learning content and system function, in an attempt to
interpret individual independent variables
horizontally and vertically. It is beneficial to the psychoanalysis of students in the online education environment. In the specific design of independent variables, the indicators of each layer are numbered in accordance with the Unicode. The specific independent variables and their appropriate indicators are shown in Table 1.
Design of dependent variables
The dependent variables are designed with the emotional and direct experience in the sensory layer as variables to define specific indicators. These variables dynamically change under the control of
the independent variables to dynamically
discriminate the psychological effects in the interactive E-learning environment. Table 2 lists the dependent variables and their appropriate
indicators.
Analysis of data results
In this questionnaire survey, undergraduate students randomly chosen from different majors and grades of the Renmin University of China are interviewed. A total of 200 questionnaires have been distributed, and 193 questionnaires are collected at a rate of 96.5%. Among them, 185 copies, 92.5% of questionnaires, are available, as required by the survey.
For the statistical results from the questionnaire survey, we make the correlation analysis as a statistical method for studying the relationship between variables using the SPSS software. In general, the Pearson correlation coefficient r, [-1,+1], is used for qualitative correlation measurement. When r is greater than 0, the variables are positively correlated with each other; When it is less than 0, there is a negative correlation between the variables; when it is close to 0, the correlation between the variables is almost null; when the absolute value of
r is close to 1, the correlation between the variables gets stronger. Therefore, in the analysis section, the relationships between intrinsic factors and between dependent and independent variables are analyzed (Hj Ramli, Alavi, Mehrinezhad et al., 2018).
(1) Correlation between intrinsic factors in the independent variables. The intrinsic factors of the independent variables mainly include four elements: interface design, interactive operations, learning content and system functions. The correlation analysis between every two elements is performed. The results from SPSS analysis of data statistics are shown in Table 3. As shown in Table 3, every two elements are all highly correlated at a coefficient of greater than 0.5. Among them, the correlation coefficient between the system function and the
learning content is 0.661, p=0.000<0.001,
representing an extremely strong correlation between them; the correlation coefficient between the interface design and the interactive operation is 0.684, and p=0.000<0.001, that is, there is a significant relationship between the two; it is therefore obvious that there is a significant correlation feature between the intrinsic elements in the independent variables.
(2) Correlation between dependent and independent variables. The correlations between the independent and dependent variables in the questionnaire are analyzed hereof. The statistical analysis results available from the SPSS software are shown in Table 4. From the statistical results in Table 4, the correlation coefficients between the
PSYCHOANALYSIS ON HUMAN-COMPUTER INTERACTION IN COLLEGE EDUCATION 197
independent and dependent variables are all greater than 0.5. It is thus proved that there is a strong correlation between them. The correlation
coefficients between interface design and
psychological elements such as emotional and sensory experience are 0.717 and 0.781, respectively, and p=0.000<0.001, representing there is an obvious relationship between them; the correlation coefficients between system functions and psychological elements such as emotional and sensory experience are 0.743 and 0.690, respectively, and p=0.000<0.001, also representing a significant relationship between them; as a result, it is proved that there is a stronger correlation
feature between independent and dependent variables.
(3) Principal results. As the results from questionnaire survey shows, the vivid teaching content and good system design rather appeal to students. In the interactive design, the humanized functions, for example, good layout, graphic presentation and timely response, can play a positive psychological effect on students, and significantly stimulate students' interests in learning and improve teaching efficiency, so that it can maximize the utilization of learning resources in the online education environment.
Table 1.
Independent variables and their corresponding indicators
Variable Index value
Interface Design
The interface of the system is simple, vivid and beautiful. Reasonable layout of system interface. Systematic Colour Matching Comfortable.
The response speed of the system is fast. System buttons and links are clear and effective.
The overall style of the system is comfortable.
Interaction operation
Easy installation of the system.
The login mode of the system is various and effective. The volume adjustment of the system is easy to operate.
The operation and flow of the system are convenient. Operational areas in the system are clearly identified and available.
Effective guidance tips for system operation. When a fault occurs, an effective solution can be found.
Every step of interactive operation of the system conforms to conventional logic.
Learning Content
The system provides rich content.
The content provided by the system is vivid. It combines pictures with text. The content provided by the system has high accuracy and no obvious errors.
The content provided by the system is easy to learn. Diversified presentation of content provided by the system. The content provided by the system meets the requirements of the outline.
Learning content meets psychological expectations.
System function
The system provides two main modules: learning and examination. Personalization and customization of the system.
The system provides comprehensive functions.
The functions provided by the system can meet the needs of students. The function of the system is simple and practical.
Table 2. Dependent variables and their corresponding indicators
Variable Index value
Emotional experience
The system is very useful and easy to use. The system is interesting and can attract students. The system has obvious characteristics of the times.
The system has strong interaction, and students can communicate with teachers timely and effectively.
More powerful learning motivation after using the system The use of the system makes learning no longer tedious.
The use of the system enhances the cooperation and communication between students.
Sensory Experience of Students
The overall use of the system is satisfactory. The system is very practical and can improve learning efficiency.
The system has a high frequency of use. The recommended frequency of the system is very high.
SHAN KONG
198
Table 3.
Statistical table of relevance analysis results of internal factors of independent variables
Interface design Interactive operation Learning content System function
Interface design
Person Relevance 1 0.684 0.509 0.612
Saliency .000 .000 .000
N 185 185 185 185
Interactive operation
Person Relevance 0.684 1 0.586 0.530
Saliency .000 .000 .000
N 185 185 185 185
Learning content
Person Relevance 0.509 0.586 1 0.661
Saliency .000 .000 .000
N 185 185 185 185
System function
Person Relevance 0.612 0.530 0.661 1
Saliency .000 .000 .000
N 185 185 185 185
Table 4.
Statistical table of relevance analysis of dependent and independent variables
Emotional experience Sensory Experience
Interface design
Person Relevance 0.717 0.781
Saliency .000 .000
N 185 185
Interactive operation
Person Relevance 0.612 0.655
Saliency .000 .000
N 185 185
Learning content
Person Relevance 0.709 0.758
Saliency .000 .000
N 185 185
System function
Person Relevance 0.743 0.690
Saliency .000 .000
N 185 185
CONCLUSION
The paper aims to tackle the defect that students' psychological factors have been neglected in the interactive online education environment. In response to the practical demands, the human-computer interaction technology may be integrated to analyze human psychology factors such as attention, memory and emotions. Then, the psychology hierarchy model is built with interactive behavior, psychological reflection and sensual experience as principal elements. The dependent and independent variables are defined and designed for questionnaire survey. The SPSS software used analyzes intrinsic elements. The results show that friendly interaction design can bring students the positive psychology effects on sensory and emotional experience, that is, a catalyst for
intriguing students’ interests in learning and
improving the teaching efficiency. It is hoped that the study can improve emotional exchange and sensory experience and other psychology behaviors in the Web-based education environment as guided by the human-computer interaction technology.
Acknowledgement
This work is supported by 2018 National Education Information Technology Research Project: Research on Development and Application of Online Course Platform Based on Oral English Flipped Classroom (186130047).
REFERENCES
Berthelsen, H., Hakanen, J. J., & Westerlund, H. (2018). Copenhagen psychosocial questionnaire-a vquestionnaire-alidquestionnaire-ation study using the job demquestionnaire-and-
demand-resources model. PloS one, 13(4), e0196450.
Hj Ramli, N., Alavi, M., Mehrinezhad, S., & Ahmadi, A. (2018). Academic stress and self-regulation among university students in Malaysia: Mediator role of mindfulness. Behavioral Sciences, 8(1), 12. Kwag, S., & Ju, B. S. (2019). Application of a Bayesian
hierarchical model to system identification of
structural parameters. Engineering with
Computers, 1-20.
McKee, L. G., Duprey, E. B., & O’Neal, C. W. (2019).
Emotion socialization and young adult
internalizing symptoms: the roles of mindfulness
and emotion regulation. Mindfulness, 1-8.
Mwiya, B., Siachinji, B., Bwalya, J., Sikombe, S., Chawala, M., Chanda, H., Kayekesi, M., Sakala, E.,
PSYCHOANALYSIS ON HUMAN-COMPUTER INTERACTION IN COLLEGE EDUCATION 199
Muyenga, A., & Kaulungombe, B. (2019). Are there study mode differences in perceptions of university education service quality? Evidence from Zambia. Cogent Business & Management, 6(1), 1579414.
Printza, A., Kalaitzi, M., Bakirtzis, C., Nikolaidis, I., Proios, H., & Grigoriadis, N. (2018). Reliability and validity of the DYMUS questionnaire for the assessment of dysphagia in multiple sclerosis (Greek version) and proposed modification.
Multiple sclerosis and related disorders, 23, 62-68.
Rafie, F., Sheibani, V., Shahbazi, M., Naghdi, N., Pourranjbar, M., & Sheikh, M. (2019). The effects of voluntary exercise on learning and memory
deficit in Parkinson’s disease model of rats. Sport Sciences for Health, 1-7.
Rahbari, A., Dehestani, M., & Baharlouei, H. (2019). Psychometric Characteristics of the Persian
Version of the Injustice Experience
Questionnaire. Psychological Injury and Law, 1-9. Rutter, L. A., Scheuer, L., Vahia, I. V., Forester, B. P., &
Germine, L. (2019). Emotion sensitivity and self‐
reported symptoms of generalized anxiety
disorder across the lifespan: A population‐based
sample approach. Brain and Behavior, (1),
e01282.
Sharpe, M. J., Stalnaker, T., Schuck, N. W., Killcross, S., Schoenbaum, G., & Niv, Y. (2019). An integrated model of action selection: distinct modes of cortical control of striatal decision
making. Annual review of psychology, 70, 53-76.
Stevenson, M. P., Schilhab, T., & Bentsen, P. (2018). Attention restoration theory II: A systematic review to clarify attention processes affected by
exposure to natural environments. Journal of
Toxicology and Environmental Health, Part B, 21(4), 227-268.
Zhang, L., Qiao, L., Che, X., Xu, M., Chen, Q., Yang, W., Qiu, J., & Yang, D. (2019). Volumetric evidence of the mediating role of mental imagery in episodic
memory effect on divergent thinking. Current
