Constructing and development of the psycho-computing traits scale: a psychometric analysis of computer users and students in the field of computer science

Figures & data

Table 1. The proposed perception to construct a scale of psycho-computing characteristics.

Concept	Factors	Indicators of psycho-computing practices
Cognitive computing: Cognitive capabilities or characteristics refer to an individual’s abilities and skills that can be attributed to their physical and mental composition, and are demonstrated by their actions and proficiency in using a computer.	Perfectionism is characterized by the following abilities: - Integrating information acquired. - Working persistently to acquire knowledge. - Achieving optimal solutions to problems. - Completing tasks.	- Constantly seeking access to the latest developments in the field of information technology. - Utilizing computer technology to store information, tasks, and instructions related to a particular topic or situation, and recalling them at later times and in different situations. - Maintaining focus and completing tasks using computer technology, despite distractions and obstacles. - Utilizing computer technology in thinking processes, idea generation, and problem-solving, while addressing various subjects. - Combining personal capabilities with computer capabilities to perform tasks quickly, accurately, and within a short timeframe. - Utilizing computer memory to collect and preserve information related to the past, present, and future, and employing it in appropriate situations. - Navigating educational materials and integrating information into online learning systems. - Analyzing educational situations and drawing conclusions about the relationships between the presented learning topics on the internet. - Sequencing online learning materials and linking them to prior knowledge. - Installing and utilizing various computer programs and applications.
Neuroticism computing: This dimension of personality is characterized by a tendency towards negative emotions and instability in daily computer practices, which reflects a negative orientation towards life. It also indicates a deficiency in self-assertion, a decrease in activity and vitality, a tendency towards depression, and a weakness in interpersonal communication.	- Sensitivity: Individuals with this trait exhibit a high degree of sensitivity and narrow-mindedness. They are hesitant to accept the opinions of others, exhibit a clear bias towards their personal opinions, and their cognitive beliefs tend to lack depth. Despite this, they prefer to use persuasion as a means to achieve their goals. - Privacy: Individuals with this trait tend to be guarded about their personal affairs, particularly in regards to interpersonal relationships. They are introverted and prefer to maintain some level of mystery about their personal lives. - Fear: Individuals with this trait are capable of accepting reality but have difficulty coping with uncertainty and the future. They experience high levels of anxiety about what the future holds for them. - Tension: Individuals with this trait are prone to becoming easily nervous and have difficulty controlling their emotions. They are characterized by excessive emotionality and high levels of nervousness. They tend to dwell on past experiences, particularly negative ones.	- Disregard for the opinions of others and a lack of influence by them in dealings through social networks. - Adherence to cognitive beliefs despite the availability of new data, information, and developments on the internet. - Strong inclination towards persuasion of others through social networks to achieve personal goals. - Reluctance to disclose personal affairs through social networks. - Limited persistence in conducting lengthy searches if desired information is not readily available through internet search engines. - Value placed on the correspondence of internet-based innovations and information technology with reality. - High levels of anxiety and tension when filling out forms or completing tasks involving the computer. - Boredom and unwillingness during prolonged periods of computer use. - Distracted navigation of internet search engines, which often results in a failure to reach the desired goal. - Appreciation for the capabilities, information, services, data, and opportunities provided by computer technology, but accompanied by a psychological struggle to determine and achieve personal goals.
Extraversion computing: An extroverted person is one who in their computer practices is interested in social relations that fulfill their libido satisfaction. They are the opposite of introverted individuals who tend to be preoccupied with their inner world of imagination and physical activity, and are relatively less capable of social participation. An extroverted person is characterized by having many friends, being impulsive, having a tendency towards fun and liveliness, being intuitive, optimistic, active, and movement-oriented. They are also known for social interaction and mingling with others.	- Good communication skills and ability to interact effectively with others. - Impulsiveness, acting on quick decisions without much forethought. - Tendency towards being lively and having fun. - Quick intuitive abilities. - Optimistic and energetic outlook. - Lack of patience. - Honesty in expressing feelings. - Tendency towards inaccuracy in execution. - Openness towards others and new experiences. - Teamwork and collaboration-oriented.	- Utilization of axioms and tacit knowledge in dealing with communication networks. - Critical interaction with ideas and topics raised through communication platforms. - Ability to communicate and achieve social interaction with others in different situations in distance learning systems. - Optimistic outlook and a desire to exert more activity and effort to solve problems and complete tasks using computer technology. - Impulsive tendencies and quick task completion using computer technology. - Focus on publishing fun and energetic video and written clips on social media platforms to spread positive energy to others. - Emphasis on completing a large amount of tasks using computer technology, often at the expense of their qualitative degrees. - Ability to learn online material even in the presence of distractions. - Keenness to participate in working groups and communicate through networks according to the needs of scientific specialization. - Publication of achievements and work on social networks.
Openness computing: One of the personality dimensions that manifests in computer practices is characterized by a love of learning and curiosity about both the internal and external worlds. Individuals with this trait are rich in experiences and have a desire to explore unfamiliar concepts. They display higher levels of both positive and negative emotions than individuals who are more closed-off. Those with this personality dimension are characterized by openness to new and unfamiliar experiences, including ideas, feelings, values, aesthetics, imagination, activities, art, and culture. They are independent in their opinions and tend to be curious by nature.	- Openness to change and the ability to accept changes that an individual may face. - Willingness to accept new and unfamiliar ideas. - Positive outlook when dealing with various technological factors. - Curiosity and a desire to learn. - Openness to new and diverse experiences. - Independence in thought and action.	- Curiosity and a love of knowledge in the face of saturation with various digital materials and products such as texts, films, and digital components. - Seeking to link digital content with personal experiences through various learning platforms and networks. - Utilizing online learning resources to discover new ways of developing knowledge and innovation processes. - Employing digital materials and resources through networks to support knowledge and innovation processes. - Taking initiative through communication networks to form new scientific connections outside of the curriculum. - Increased open-mindedness due to exposure to new ideas through social networks. - Utilizing various digital means of expression (e.g. sound, image, symbols) to express intellectual independence and personal opinions. - Agreement, response, and anticipation of various technological changes and innovations. - Utilizing digital resources to face and accept different life changes. - Shaping imagination and aesthetic values through the use of digital materials and resources.
Dynamic computing: Dynamic Computing refers to the characteristics of an individual’s computational practices that are related to their motives and physical aptitudes, abilities, or needs.	- Adventure-seeking and a tendency towards taking risks. - Ability to challenge and overcome difficulties. - Competitiveness, particularly in risky situations. - High levels of self-confidence in their abilities. - Ability to form strong relationships in which they are the center of attention.	- Utilizing distance learning platforms to identify pre and post-learning requirements and performance appraisal criteria in order to build positive expectations and achieve success. - Utilizing ICT to enhance learning and become a self-directed learner. - Preferring challenging work through learning networks. - Ability to complete assigned tasks without guidance from others through learning networks. - Seeking to take advantage of educational experiences and opportunities offered through learning networks to increase competitiveness and chances of success. - Keenness to participate in networking groups and striving to be effective and the center of attention in all tasks, activities, and learning processes. - Recognizing the importance of employing innovations and applications of scientific material in various fields through learning networks. - Utilizing audio, text, video, static, and animation files to diversify the presentation of scientific content through learning networks.
Mastery computing: The individual’s computer practices are characterized by a high level of attentiveness, avoidance of indifference, a capacity for commitment, relentless pursuit of goals, and a focus on investing efforts for personal benefit.	- Logical thinking: The ability to act successfully in various situations by finding logical connections between problematic situations to identify the best solutions. - Mindfulness: The practice of meditation to control unruly and uncontrolled thoughts and behaviors, increasing mental alertness, and reducing stress by improving focus and reducing the tendency to move rapidly from one idea to another. - Self-reliance: Preference for working alone and not relying on support from others, which often leads to high grades in educational settings. - Control: The ability to control the course of events and negative emotions, with a preference for leadership and control in various matters. Distinguished by the ability to direct others and exploit their abilities and capabilities.	- Exploring learning networks to access expected learning outcomes through the objectives of the digital course. - Accessing live digital models and drawings through learning networks to develop and master certain skills. - Making connections between knowledge and concepts learned through learning networks. - Regularly reviewing scientific material through learning networks to discover relationships between different parts. - Utilizing digital content elements (e.g. infographics, e-books, mind maps) to support achievement of goals with minimal effort. - Ability to distinguish between truth and opinion on topics raised through communication networks and judge ongoing discussions. - Ensuring credibility and reliability of digital materials (texts, films, visual components) and presenting views and justifications logically. - Ability to install and use software application packages, create plans to complete assigned tasks, and successfully complete required activities. - Feeling a degree of control over the learning process through learning networks, with success being a direct result of effort expended. - Benefitting from immediate and delayed feedback through learning networks to support correct responses and correct incorrect responses. - Utilizing effective learning styles across learning networks for future learning topics and situations. - Reviewing unsatisfactory parts of completed tasks through learning networks. - Anticipating difficulties and obstacles that may arise in learning processes through learning networks.

Table 2. Some indicators and coefficients of construct validity.

Constructs	Items	Loading Factor	Macdonalds Omega	CR	AVE	$\sqrt{\mathrm{A}\mathrm{\text{VE}}}$
Cognitive computing (AvTC)	10	0.49-0.77	0.873	0.870	0.504	0.710
Neuroticism computing (AvTN)	10	0.60-0.73	0.892	0.893	0.595	0.771
Extraversion computing (AvTE)	10	0.67-0.79	0.923	0.921	0.539	0.734
Openness computing (AvTO)	10	0.69-0.82	0.926	0.926	0.558	0.747
Dynamic computing (AvTD)	8	0.54-0.82	0.903	0.901	0.533	0.730
Mastery computing (AvTM)	10	0.53-0.78	0.900	0.899	0.513	0.716

Table 3. Item Fit Analysis for Psycho-computing scale.

Items	Measure	Model S.E	Infit MNSQ ZSTD		Outfit MNSQ ZSTD		Pt-measure CORR
TM1	0.36	0.18	1.49	1.9	1.49	1.9	0.46
TM2	0.22	0.17	1.40	1.9	1.47	2.0	0.45
TD8	0.05	0.18	1.49	1.8	1.28	1.0	0.47
TD7	0.08	0.20	1.49	0.8	1.43	0.2	0.46
TM10	0.14	0.16	1.48	2.0	1.46	1.9	0.46
TM3	0.07	0.16	1.49	1.2	1.37	0.7	0.50
TM4	0.26	0.19	1.44	1.3	1.32	0.1	0.57
TM9	0.29	0.17	1.49	2.2	1.38	0.6	0.60
TM7	0.35	0.17	1.49	0.3	1.26	1.4	0.60
TD6	0.04	0.20	1.47	0.0	1.25	0.1	0.61
TM6	0.11	0.18	1.32	0.4	1.32	0.8	0.63
TM5	0.34	0.16	1.41	1.4	1.31	0.5	0.63
TD1	0.52	0.19	1.36	0.4	1.06	0.3	0.63
TM8	0.23	0.18	1.23	0.1	1.19	0.3	0.64
TD2	0.57	0.19	1.31	0.2	0.87	0.8	0.64
TD4	0.17	0.19	1.28	0.5	1.04	0.3	0.64
TD5	0.35	0.19	1.21	0.4	1.06	1.1	0.65
TD3	0.15	0.20	1.20	0.5	0.81	1.3	0.65
TC5	0.46	0.15	1.11	0.6	1.06	0.4	0.65
TO8	0.06	0.19	0.80	1.1	0.72	1.8	0.65
TO9	0.08	0.19	0.78	1.2	0.70	0.2	0.66
TN4	0.03	0.17	0.99	0.0	0.87	1.1	0.66
TO10	0.15	0.18	1.21	1.1	1.46	0.3	0.66
TC8	0.09	0.18	1.03	0.2	1.03	0.9	0.66
TE4	0.46	0.17	1.05	0.3	1.25	0.7	0.66
TC2	0.44	0.18	0.98	0.0	0.93	0.0	0.67
TC10	0.23	0.20	0.88	0.6	0.79	2.0	0.67
TC6	0.17	0.20	0.89	0.6	0.83	0.4	0.67
TO7	0.09	0.18	0.94	0.2	0.98	0.1	0.67
TC3	0.35	0.19	1.12	0.2	1.48	0.6	0.67
TC1	0.35	0.19	0.89	0.5	0.90	0.3	0.67
TN1	0.26	0.19	1.16	0.4	1.00	0.7	0.67
TN9	0.18	0.20	0.92	0.3	0.85	0.5	0.68
TN3	1.01	0.18	1.17	0.9	1.06	0.6	0.68
TE3	0.21	0.18	0.79	1.2	0.83	1.2	0.68
TN2	0.25	0.16	0.91	0.2	0.86	1.6	0.68
TO5	0.14	0.17	0.97	0.3	0.87	0.6	0.69
TE2	0.46	0.18	0.79	1.2	0.74	0.5	0.69
TE5	0.26	0.18	0.70	1.6	0.66	0.2	0.69
TC4	0.31	0.21	0.89	0.5	0.87	1.2	0.69
TE6	0.43	0.16	0.93	0.3	0.87	2.1	0.69
TC7	0.28	0.16	0.89	0.0	0.94	1.5	0.69
TO3	0.41	0.19	0.78	1.1	0.74	0.3	0.69
TN8	0.30	0.17	0.84	0.8	1.52	2.4	0.70
TN10	0.04	0.18	0.74	1.3	0.68	0.4	0.70
TE8	1.03	0.18	0.85	0.2	0.95	2.1	0.70
TO6	0.09	0.19	0.61	2.1	0.57	1.6	0.73
TN7	0.24	0.18	0.60	0.5	0.93	0.6	0.73
TO1	0.05	0.18	0.77	1.8	0.72	0.7	0.74
TO2	0.37	0.18	0.75	1.6	0.71	0.2	0.69
TN6	0.12	0.16	1.15	0.2	1.02	0.7	0.69
TO4	0.38	0.17	0.78	0.2	0.73	0.5	0.69
TC9	0.13	0.18	0.74	0.5	0.75	0.6	0.70
TN5	0.28	0.18	0.72	0.4	0.74	1.2	0.70
TE1	0.06	0.21	0.73	0.3	0.73	1.6	0.70
TE10	0.03	0.16	0.67	0.9	0.56	0.6	0.73
TE9	0.02	0.16	0.66	1.2	0.82	0.5	0.73
TE7	0.06	0.16	0.66	0.2	0.56	0.2	0.74

Table 4. Item dimensionality of Psycho-computing scale.

	Empirical		Modeled
Total raw variance in observations	81.0	100%		100%
Raw variance explained by measures	43.0	46.4%		46.6%
Raw variance explained by persons	8.5	10.5%		10.6%
Raw Variance explained by items	14.5	17.9%		18.0%
Raw unexplained variance (total)	58.0	71.6%	100%	71.4%
Unexplained variance in 1st contrast	12.4	11.5%	30.0%
Unexplained variance in 2nd contrast	2.8	3.5%	4.8%
Unexplained variance in 3rd contrast	2.4	3.0%	4.2%
Unexplained variance in 4th contrast	2.3	2.8%	3.9%
Unexplained variance in 5th contrast	2.1	2.6%	3.6%

Table 5. Person and Item separation and reliability for Psycho-computing scale.

					Infit		Outfit
	Score	Count	Measure	Error	MNSQ	ZSTD	MNSQ	ZSTD
Mean	223.8	58.0	0.90	0.16	1.03	−0.3	1.03	−0.3
S.D	32.0	0.0	0.76	0.06	0.54	1.9	0 .54	1.9
Real rmse	0.19
Adj. sd	0.73
Separation	3.83
Person reliability	0.94
Mean	1740.0	722.0	0.00	0.05	1.00	−0.4	1.03	−0.1
S.D	65.3	0.0	0.18	0.01	0.30	2.3	0.43	2.2
Real rmse	0.06
Adj. sd	0.17
Separation	3.03
Item reliability	0.90

Table 6. The results of the exploratory factor analysis using Promax method.

Component	Initial eigenvalues
	Total	% of Variance	Cumulative %
Cognitive computing (AvTC)	3.554	59.238	59.238
Neuroticism computing (AvTN)	1.708	28.471	87.709
Extraversion computing (AvTE)	1.265	4.416	92.125
Openness computing (AvTO)	1.197	3.283	95.409
Dynamic computing (AvTD)	1.157	2.612	97.020
Mastery computing (AvTM)	1.119	1.980	98.134

Figure 1. Results of the confirmatory factor analysis of the model adopted for the relationship of the scale items to its dimensions.

Table 7. Confirmatory factor analysis outcomes regarding the adopted model’s fit to the relationship between scale items and their respective dimensions.

Name of category	Indicators of the internal construct validity	Level of acceptance	Indexes in the proposed model
Absolute fit	ChiSq	P > 0.05	Significant
	RMSE	RMSE < 0.08	.077
Incremental fit	CFI	CFI > 0.90	.903
	TLI	TLI > 0.90	.914
	NFI	NFI > 0.90	.926
Parsimonious fit	Chisq/df	Chis/df < 5.0	Chisq/df = 4.327 < 5.0

Table A. Number of items omitted in the psycho-computing traits scale based on experts.

No	Dimensions	Number of items in the initial copy	Number of items omitted	Number of modified items
1	cognitive computing	11	1	3
2	neuroticism computing	12	2	5
3	extraversion computing	11	1	4
4	openness computing	10	0	2
5	dynamic computing	11	3	4
6	mastery computing	10	0	4
Total		65	7	22

Table B. Item fit analysis for psycho-computing traits scale (initial).

Items	Measure	Model S.E	Infit MNSQ ZSTD		Outfit MNSQ ZSTD		Pt-measure CORR EXP
TM10	0.27	0.13	1.44	6.3	1.57	7.4	0.12	.27
TM1	0.18	0.13	1.43	5.7	1.45	5.5	0.16	.18
TD8	0.43	0.14	1.32	5.0	1.36	5.2	0.17	.43
TD7	−0.12	0.14	1.45	5.9	1.53	6.2	0.18	−.12
TC11	0.04	0.15	1.51	3.5	1.62	4.1	0.19	.04
TE12	−0.60	0.15	1.48	3.8	1.59	5.3	0.20	−.60
TN11	−0.60	0.15	1.53	4.1	1.79	4.7	0.21	−.60
TO8	0.19	0.13	1.44	3.6	1.49	3.8	0.23	.19
TD9	0.76	0.13	1.34	4.7	1.50	4.3	0.25	.76
TD11	0.37	0.13	1.32	2.7	1.36	3.3	0.28	.37
TE11	0.53	0.13	1.31	2.9	1.48	2.6	0.30	.53
TC12	0.66	0.14	1.25	2.2	1.40	3.6	0.32	.66
TD1	−0.09	0.14	1.07	0.4	1.03	0.4	0.59	−.09
TM8	−0.25	0.15	1.04	−0.3	1.06	0.3	0.59	−.25
TD2	0.37	0.13	0.98	−1.1	0.93	0	0.59	.37
TD4	−0.28	0.13	1.08	1.4	1.09	0.4	0.59	−.28
TD5	−0.37	0.14	1.2	−1.5	1.09	0.5	0.60	−.37
TD3	0.42	0.15	0.96	1.2	0.96	−0.1	0.62	.42
TC5	−0.19	0.13	1.02	0.2	1.07	0.3	0.62	−.19
TO11	0.08	0.14	1.05	0.2	1.08	0.1	0.63	.08
TO9	0.77	0.15	0.97	0.1	0.91	−0.1	0.63	.77
TN4	0.16	0.14	1.06	0.3	1.88	1.3	0.64	.16
TO10	−0.38	0.13	0.95	0	1.04	0.2	0.65	−.38
TC8	0.51	0.13	1.08	0.5	1.11	0.6	0.64	.51
TE4	0.01	0.14	1.05	0.3	1.06	0.3	0.65	.01
TC2	0.25	0.14	1.01	0.1	1.01	0.1	0.66	.25
TC10	0.17	0.15	0.96	0.1	0.88	−0.1	0.65	.17
TC6	0.23	0.14	1.02	0.2	0.95	−0.1	0.66	.23
TO7	−0.18	0.13	1.05	0.3	0.90	−0.1	0.65	−.18
TC3	−0.48	0.13	1.08	0.4	0.90	0.3	0.65	−.48
TC1	0.04	0.14	0.95	0.1	0.73	−0.3	0.66	.04
TN1	−0.27	0.14	0.87	1.1	0.66	1	0.68	−.27
TN9	0.61	0.15	1.03	0	0.75	−0.4	0.67	.61
TN3	−0.21	0.14	0.93	−0.2	0.78	−0.2	0.67	−.21
TE3	−0.33	0.13	0.95	−1.2	0.77	−0.1	0.68	−.33
TN2	0.29	0.13	0.94	−0.3	0.78	−0.5	0.68	.29
TO5	−0.34	0.14	0.91	−0.2	0.63	−0.2	0.67	−.34
TE2	−0.09	0.14	0.79	0.1	0.83	−0.4	0.67	−.09
TE5	−0.02	0.15	0.87	−0.2	0.71	−0.3	0.69	−.02
TC4	−0.02	0.14	0.87	−1.4	0.71	−0.6	0.68	−.02
TE6	−0.34	0.13	0.81	−0.3	0.65	−0.4	0.71	−.34
TC7	−0.36	0.13	0.78	−0.4	0.65	−0.8	0.71	−.36
TO3	−0.10	0.14	0.68	−1.6	0.64	−0.6	0.72	−.10
TN8	0.26	0.17	0.84	0.8	1.52	2.4	0.71	0.70
TN10	0.03	0.18	0.74	1.3	0.68	0.4	0.70	0.66
TE8	1.03	0.18	0.95	0.2	0.92	2.1	0.70	0.69
TO6	0.09	0.19	0.61	2.1	0.56	1.6	0.71	0.66
TN7	0.25	0.18	0.90	0.5	0.90	0.6	0.71	0.72
TO1	0.02	0.18	0.67	1.8	0.62	0.7	0.72	0.68
TO2	0.26	0.18	0.70	1.6	0.66	0.2	0.68	0.64
TN6	0.51	0.16	1.15	0.2	1.06	0.7	0.68	0.65
TO4	0.26	0.17	0.78	0.2	0.83	0.5	0.69	0.70
TC9	0.03	0.18	0.94	0.5	0.86	0.6	0.71	0.66
TN5	0.51	0.18	0.93	0.4	0.87	1.2	0.73	0.69
TE1	0.26	0.21	0.79	0.3	0.74	1.6	0.73	0.66
TE10	0.03	0.16	0.70	0.9	0.66	0.6	0.75	0.72
TE9	0.51	0.17	0.78	1.6	0.56	0.6	0.76	0.68
TD12	0.35	0.17	0.91	0.3	0.61	0.4	0.76	0.64
TM11	0.05	0.16	0.67	0.5	0.74	0.5	0.77	0.63
TD6	0.01	0.16	0.67	0.5	0.71	0.4	0.77	0.63
TM12	0.19	0.16	0.62	0.5	0.70	0.5	0.78	0.64
TD3	0.25	0.16	0.61	0.4	0.68	0.3	0.78	0.64
TE7	0.20	0.15	0.61	0.5	0.64	0.3	0.79	0.62
TD10	028	0.16	0.61	0.3	0.61	0.4	0.79	0.61

Table C. Item dimensionality of psycho-computing traits scale.

	Empirical		Modeled
Total raw variance in observations	101.1	100%		100%
Raw variance explained by measures	25.1	35.1%		25.0%
Raw variance explained by persons	8.5	8.5%		8.5%
Raw Variance explained by items	16.6	16.4%		16.5%
Raw unexplained variance (total)	76.0	75.2%	100%	75.0%
Unexplained variance in 1st contrast	21.5	21.3%	28.3%
Unexplained variance in 2nd contrast	7.2	7.1%	9.4%
Unexplained variance in 3rd contrast	2.9	2.9%	3.8%
Unexplained variance in 4th contrast	2.5	2.5%	3.3%
Unexplained variance in 5th contrast	2.4	2.4%	3.1%

Table D. Person and item separation and reliability for psycho-computing traits scale.

					Infit		Outfit
	Score	Count	Measure	Error	MNSQ	ZSTD	MNSQ	ZSTD
Mean	295.5	70.0	0.83	0.14	1.04	−0.3	1.04	−0.3
S.D	37.7	0.0	0.68	0.05	0.49	2.0	0.49	2.0
Real rmse	0.17
Adj. sd	0.66
Separation	3.94
Person reliability	0.94
Mean	683.0	150.0	0.00	0.05	1.00	−0.3	1.04	0.1
S.D	54.3	0.0	0.18	0.01	0.27	2.1	0.35	2.7
Real rmse	0.06
Adj. sd	0.18
Separation	3.15
Item reliability	0.91

Table E. The psycho-computing traits scale.

1	Gender	□ Male
		□ Female
2	Specialization	□ Scientific
		□ Literary
3	The duration of daily computer technology usage:	□ Less than an hour
		□ Less than two hours
		□ Less than four hours
		□ Four hours or more
4	I use computer technology in areas (you are allowed to choose more than one answer)	□ Scientific knowledge in the field of specialization
		□ General cultural
		□ Social
		□ Religious
		□ Entertainment
		□ Other

Table

No	Item	Completely applicable	Applicable	Almost	Not applicable	Completely not applicable
The first dimension: cognitive computing
1	I possess the proficiency to utilize computer technology to store and retain information, tasks, and instructions pertaining to a specific topic or situation, enabling me to recall them accurately and apply them in different scenarios.
2	Despite distractions and challenges that may arise, I maintain a consistent focus on task completion using computer technology, ensuring efficient progress despite external factors.
3	I leverage computer technology to facilitate thinking processes, generate ideas, and solve problems in diverse ways while addressing a given topic.
4	By harnessing the combined capabilities of both myself and computer systems, I can effectively perform tasks and achieve accurate and swift completion.
5	I capitalize on the memory support offered by computers to gather and store information relevant to the past, present, and future, utilizing it appropriately in the relevant context and situation.
6	I possess the ability to navigate through online learning materials and seamlessly integrate the acquired information into the online learning system.
7	I analyze educational situations and establish connections between them and the specific learning topics presented online, fostering a deeper understanding of the content.
8	I demonstrate the ability to effectively sequence and organize online learning materials, integrating them with my existing knowledge base for enhanced comprehension and retention.
9	I am capable of installing and proficiently utilizing a diverse range of computer programs and applications, adapting to different technological tools as needed.
10	I effectively employ computer technology to memorize and retain information, tasks, and instructions related to specific topics or situations, allowing for subsequent recall and application in various contexts.
The second dimension: Neuroticism computing
1	I demonstrate independence in my online interactions, as I do not consider or allow the opinions of others to influence my actions and behavior on social media platforms.
2	I exhibit a strong adherence to my cognitive beliefs, irrespective of the availability of new data, information, and technological advancements on the internet.
3	My drive to achieve goals is characterized by a compelling desire to persuade others through social media platforms, advocating for specific topics or causes.
4	I have a tendency to maintain privacy regarding personal matters and avoid disclosing them on social media platforms.
5	I prefer not to engage in prolonged and continuous searches if I cannot directly obtain the desired information through search engines on the internet.
6	My interest in innovations and information technology via the internet is limited to their compatibility with the realities of our daily lives.
7	When faced with the task of filling out forms, such as job applications or competition registrations, I experience heightened anxiety and nervousness due to the fear of making mistakes.
8	Prolonged use of the computer for tasks often leads to feelings of boredom and monotony.
9	While I initially intend to conduct focused online searches for specific information, I often find myself becoming easily distracted and failing to achieve the desired goal.
10	I am fascinated by the vast capabilities, information, services, data, and opportunities offered by computer technology. However, this fascination can sometimes lead to a psychological struggle in defining and achieving my objectives.
The third dimension: Extraversion computing
1	When dealing with networks, I rely on intuition and tacit knowledge as a basis for my decision-making and actions.
2	I engage in critical analysis and evaluation of ideas and topics presented on social media platforms, promoting a thoughtful and discerning interaction.
3	I possess the ability to effectively communicate and engage socially with others in various situations within distance learning systems.
4	I maintain an optimistic outlook and demonstrate a willingness to invest additional effort and activity in problem-solving and task completion through the utilization of computer technology.
5	I tend to exhibit impulsiveness and a preference for swift task completion when using computer technology.
6	I actively strive to share engaging and lively video and written content on social media platforms, aiming to spread positive energy to others.
7	My focus primarily lies on the quantity of tasks completed using computer technology, rather than solely prioritizing quality.
8	Despite the presence of distractions, I possess the capability to learn effectively from online materials.
9	I actively seek to participate in work groups and engage in network-based communication, aligning with the specific requirements of my field of study or professional specialization.
10	I make a deliberate effort to showcase and publicize my achievements and work on social media platforms.
The fourth dimension: Openness computing
1	I possess a deep curiosity and a broad range of knowledge regarding the saturation of diverse digital materials and products, such as texts, films, and digital components.
2	I actively seek to establish connections between the offerings of digital content and my own experiences through various learning platforms and networks.
3	Online learning resources play a crucial role in assisting me in exploring new approaches and formulating innovative action plans pertaining to specific topics.
4	I leverage digital materials across networks to foster knowledge acquisition and innovation processes.
5	Through social networks, I proactively initiate the formation of new scientific connections that extend beyond the boundaries of the prescribed curriculum.
6	The exposure to novel ideas via social networks contributes to my development of an open-minded perspective.
7	The diverse digital means of expression, including sound, images, and symbols, enable me to demonstrate intellectual independence and express my own opinions.
8	I consistently embrace and eagerly anticipate various technological changes and innovations.
9	Digital resources serve as valuable tools for me to confront and adapt to various life changes.
10	The availability of digital materials and resources greatly supports the cultivation of my imaginative abilities and the development of my aesthetic values.
The fifth dimension: Dynamic computing
1	I actively survey distance learning platforms to gain a comprehensive understanding of the prerequisites, learning objectives, and assessment criteria, allowing me to develop positive expectations and achieve success.
2	The utilization of Information and Communication Technology (ICT) empowers me to enhance my learning experience and become a self-directed learner.
3	I tend to gravitate towards challenging tasks and assignments available through learning networks, as they stimulate my intellectual growth.
4	I possess the capability to independently complete assigned work without requiring guidance or assistance from others, leveraging the resources and support provided by learning networks.
5	I actively seek to capitalize on educational experiences and opportunities presented through learning networks to enhance my competitive skills and increase my chances of success.
6	I actively engage in networking groups and strive to be highly effective in all tasks, activities, and learning processes, recognizing the value of collaboration and collective learning.
7	I recognize the significance of incorporating innovative approaches and applications of scientific course material across various domains, employing learning networks as a platform for implementation.
8	I leverage a diverse range of media formats, including audio, text, video, and still and animation files, to ensure the delivery of scientific content is engaging and varied across learning networks
Sixth Dimension: Mastery Computing
1	Within learning networks, I actively explore and engage with digital course objectives to ensure the attainment of expected learning outcomes.
2	I leverage learning networks to gain access to live digital models and drawings that aid in the development and mastery of specific skills.
3	Utilizing learning networks, I consistently review scientific material to uncover the interconnectedness and relationships among its various components.
4	Digital content elements, such as infographics, electronic books, mind maps, and other resources, play a pivotal role in supporting me in achieving my goals with minimal effort.
5	I possess the ability to discern between factual information and subjective opinions concerning topics discussed on social networks, enabling me to make informed judgments during ongoing discussions.
6	I prioritize the credibility and reliability of digital materials, including texts, films, and visual components, and present my views and justifications in a logical and coherent manner.
7	Through learning networks, I actively seek and benefit from both immediate and delayed feedback, which aids in reinforcing correct responses and modifying incorrect ones.
8	I apply proven learning techniques discovered within learning networks to future learning topics and situations, replicating successful strategies for optimal outcomes.
9	Upon completion of any assignment within learning networks, I diligently review and reflect upon the parts that I found unsatisfactory, aiming for continuous improvement.
10	I proactively anticipate potential difficulties and obstacles that may arise during the learning process within learning networks, allowing me to better navigate and overcome challenges.

Data availability statement

The authors declare that all other data supporting the findings of this study are available within the article and its supplementary information files. Informed consent was obtained from all individual participants included in the study.