Technophilia or technophobia: The unified model of the paradox of older adults’ digital learning

doi:10.21203/rs.3.rs-3893255/v1

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Research Article

Technophilia or technophobia: The unified model of the paradox of older adults’ digital learning

https://doi.org/10.21203/rs.3.rs-3893255/v1

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Background: Previous research investigating technology adoption has emerged prominently; however, little has been done with older adults’ approach-avoidance conflict toward digital learning. To fulfill the need of accumulating older adult learners, the current research comprehensively incorporates all target-specific elements related to the process of digital learning for older adults. Particularly, the unified model highlights barrier factors and offers insights into the nature of their paradoxical hesitation towards technology.

Methods: In this study, a total of 20 older adults (mean age 63.85 and 25% male) were interviewed. Interviews were recorded for thorough analysis. The coding framework guided data analysis to achieve research objectives.

Results: The findings revealed that: (1) social influence was found as older adults’ major precursor of exposure to digital technology; (2) both acceptance and barrier factors emerged regarding older adults’ digital learning; (3) older adults feature paradoxical hesitation towards technology; (4) three types of senior digital learners were identified: tech-native learners; tech-novice learners; tech-rejector learners.

Conclusions: The unified model of the paradox of older adults’ digital learning was created, highlighting barrier factors and offers insights into the nature of their paradoxical hesitation towards technology. This study contributes a reference for elderly digital learning field and serving the accumulated number of older adult learners.

Adult learning

Approach-avoidance conflict

Barrier factors

Paradoxical hesitation towards technology

With the trend of population aging, Taiwan, which has entered an aging society, is also gradually paying increasing attention to the learning and quality of life of the elderly (e.g., 1, 2, 3). Also, the use of technology among older adults in the current years has risen increasingly (4, 5). Accordingly, there have been numerous international research studies conducted on the digital use of the elderly (e.g., 6, 7–10). It is therefore clear that the issue of how digital technology can help to improve the lives of older people is a crucial and continuing high-demand issue.

Despite the increasing usage of technology among the elderly and the crucial role that digital learning has been found to play in enhancing the integration of older adults into their lives and learning (11, 12), there has been little research focusing on both acceptance and rejection of older adults’ digital learning. Previous research has indicated that participating in digital learning offers more significant positive benefits for the elderly (10, 13, 14). Nevertheless, before discussing the performance of older adults’ digital learning, the premise is that we should understand whether digital learning is interesting or terrifying, or whether older adult learners may have paradoxical hesitation toward digital learning.

Therefore, to shed light on the mechanisms behind a growing number of older adult learners who participate in digital learning, the current research aims to propose a theory entirely tailored made for older adult learners during digital learning. As a prerequisite, the current framework tries to integrate and unify all the elements and sequences that feature older adults’ specific situations regarding the process of digital learning involving precursors, the acceptance and barrier factors, intentions, perceived behavioral controls, and outcomes and behaviors.

1.1 Motivation and acceptance of digital learning for older adult learners

The Technology Acceptance Model (TAM; 15) is a theory that described how and why users come to accept and adopt technology. In TAM, perceived usefulness and Perceived ease of use have been showed to have a positive relation to intentions and actual behaviors. To extend TAM, several theories were created to further model this process regarding technology adoption, such as Unified Theory for Acceptance and Use of Technology (UTAUT 1&2) (16, 17). However, so far, few theories specifically tailored for targeting the elderly have been developed regarding technology or digital learning. When it comes to technology use or even digital learning, the elderly exhibit distinct motivation, learning patterns, and adaptation after being exposed to digital learning. Target specific characteristics and theories are a trend and urgent need with accumulating aging populations.

To discuss whether older adults participate in digital learning or not, we can start with reviewing older adults’ digital using circumstance. Hutto, Bell (18) indicated that self-efficacy is the mediator of older adults’ intention to use social media. Therefore, before discussing whether older adults willing to use digital techniques, we have to encourage older adults to participate in digital learning and it is important to address their concerns about "difficulty," "unfamiliarity," and "fear of falling behind." Instead, we should cultivate positive attitudes and mental states, such as "ease of use" and "sense of achievement" about using digital technologies. Moreover, the benefits of incorporating digital techniques into their daily life are also important factors in promoting the success of older adults. For example, Jung, Walden (19) investigated the reason of whether older adults use Facebook or not, and the result shows that the reason of older adults using Facebook includes “the ability to contact with people who usually cannot be contacted”, “the ability to share photos”, “the ability to be contacted by families and friends and social surveillance” and “the convenience to organize and communicate with social network”. In addition, by analyzing a series of qualitative interviews, Lüders and Gjevjon (20) found that the motivation of older adults to use digital techniques can be enhanced by several factors, such as the belief that "if my grandchildren can do it, so do I," followed by curiosity, awareness of the multiple functions of digital devices, and social interaction.

1.2 Barriers hindering the elderly from digital learning

Although many theories aim to extend TAM, few of them specifically discuss the barriers that hinder the use of technology or participation in digital learning. In fact, previous research has already indicated some obstructive factors or barriers regarding technology adoption or digital learning (e.g., 21, 22, 23). For example, Verkasalo, López-Nicolás (22) brought up a model and emphasized that some technical barriers can weaken the motivation of using technology. These technical barriers are based on different devices and specific, so they tried to distinguish the devices in this model and invited the user and non-users of these devices to participate in the experiment to confirm this model. Moreover, Hutto, Bell (18) and Jung, Walden (19) indicate that interface design and privacy protection are one of the obstructive factors of older adults using social media and digital technology.

In addition, through qualitative interviews, Lüders and Gjevjon (20) found that if older adults make an observation or social comparison through digital devices and feel socially excluded, then this would weaken their motivation to use digital devices. Seifert, Hofer (24) also pointed out that it is likely for older adults to feel socially excluded on the internet and this make them more unwilling to use the internet. Besides the issue of privacy protection and social comparison, the biggest problems are still the lack of digital competency and difficulty to use. For example, Jung, Walden (19) mentioned that the reasons for older adults’ unwillingness to use Facebook include the need for media richness, cue absent aspects of Facebook, unwillingness to spend time to get familiar with Facebook, and limited site skills. Research has also indicated that infrequent use of digital techniques among older adults hinders their ability to use them freely and leads to unfamiliarity with their operation, this in turn, can result in feelings of computer anxiety and technological fear (25). Although digital technology is crucial in improving the quality of life, a significant portion of adults and older adults lack basic digital competencies or skills. This knowledge gap creates a division between them and the younger generation, often referred to as digital natives, resulting in a phenomenon known as the generation gap. Oppenauer-Meerskraut, Kropf (26) investigated gaming design for older adults’ physical training also indicated that older adults might reject digital or gaming design.

To conclude, both acceptance and barrier factors are crucial for older adults regarding digital learning. The current research accordingly aims to explore older adults’ demands by weighting equally on both acceptance and barrier factors.

1.3 Approach-avoidance conflict in digital learning for the elderly: paradoxical hesitation towards technology

Approach-avoidance conflict refers to a conflict arises when people have two opposing psychological forces toward a certain object: approach and avoidance. Approach means pushing them toward a certain goal or having positive and desirable aspects toward the object. Avoidance refers to a force pulling them away from or having negative or undesirable force toward the object (27, 28).

As for approach force, the previous research on the usage of technology have primarily focused on the acceptance factors for general consumers, workers, and young people (e.g., 16, 17, 29). However, there are few discussions about the avoidance force or mental paradox of older adults while using digital technique. Young people or the workforce generally have a higher frequency and need for using technology compared to older adults, resulting in less mental paradox and shorter break-in periods. Previous research has also shown that older adults experience mental paradoxes when using technology (30, 31). For example, Wilson (32) investigated the relation between older adults’ emotional attachment towards a device and happiness showed that the increase of the frequency of using smartphone would strengthen the emotional attachment towards smartphone and raise their self-esteem. However, excessive emotional attachment to the device was found to reduce the sense of belongingness among older adults. Therefore, older adults should find the balance between “the increase of self-esteem by digital device using” and “the decrease of belongingness by deuced emotional attachment towards devices”.

1.4 Older adults digital learning outcomes and behaviors

Previous research on the outcome performance or learning behaviors of older adults’ digital technique using found out that the good or bad of the performance depends on how they use digital technique during the process and their attitude toward technology and. For example, Tirado-Morueta, Aguaded-Gómez (33) indicated that previous research on the acceptance of individuals toward technique just simply looked into whether they “accept it or not”. They thought that the performance of individual’s technique using should divided into three dimensions, the accessibility of physical distance, the frequency of use, and the purpose of using technology, which concluded three levels of access and use of technology: physical access, operational use, and informative-expressive use. In their research, physical access refers to the usage frequency; operational use means performing simpler task used for our daily life; informative-expressive use refers to more difficult tasks that require a higher level of skills.

Furthermore, the degree to which older people adapt to digital technology also depends on whether they are actively participating in society or only passively observing it. For example, previous research on older adults’ motivation and mental adaptation on using social media found that if older adults made directed communications with families or other social objects via Facebook, the decrease of loneliness and the increase of satisfaction of their social role were greater than those who made broadcast communications or just passively consumed the content (18). The discussion above can also apply on whether older adults initiatively participate in digital learning (for example, initiatively raise a question online or share knowledge) or passively participate in digital learning (for example, simply view websites for knowledge or listen to online courses).

Lastly, older adults’ attitude toward technique and the role technique plays in their lives also influence on whether they adapt to digital learning well or not. Hutto, Bell (18) indicated that older adults’ attitude toward digital technique should be as “augments” of daily life but not “replacements”. By doing so, older people can better adapt to the use of technology.

As discussed above, this research considers different levels of digital learning outcomes and behaviors by classified older adults as three types of learners based on (a) whether if digital learning is an autonomous choice; (b) whether if technology is regarded as augments to enhancing their life or as replacements of their original life; and (c) whether if high-level functions of technology were employed to assist daily needs.

1.5 Current study

The purpose of this study is to develop a new theory entirely customized especially for older adults while participating in digital learning. The current research adds several target specific elements in this framework, inclusive of barrier factors and paradoxical hesitation intention toward digital learning. Moreover, the current study unifies all elements and situations that emerge throughout the whole older adults’ digital learning process. The sequences from mechanisms how they are exposed to technology to classifying types of older adults’ digital learning behaviors are also analyzed thoroughly.

At this point, the research questions addressed are:

1. What is the major precursor of exposure to technology for the elderly?

2. Are there acceptance and barrier factors when it comes to senior digital learning?

3. Is it possible that older adults have paradoxical hesitation intention toward digital learning, in addition to having intention to use and having no intention to use it?

4. What are their perceived behavioral controls during the process of digital learning?

5. What are their actual learning behavioral types?

2.1 Participants

The study recruited 20 elderly people (5 men and 15 women) in the Taiwanese community. The participants aged between 50 and 77 years old (mean age: 63.85; SD:6.94). All participants indicated themselves as mobile phone active users and were familiar with the functions as they use technology in their daily lives. The basic information and numbers of the participants are shown in Table 1.

Table 1

*Basic information and characteristics of participants*
ID	Gender	Age	Commonly used technology products	Average time spent using technology products per day (hours)
0517A	Female	69	smartphone, tablet & computer	6
0518A	Male	50	notebook, computer & smartphone	8
0519A	Female	77	smartphone	2 ~ 3
0519B	Male	65	computer & smartphone	never left except for bedtime
0525A	Female	60	computer & smartphone	13
0601A	Female	51	smartphone, tablet & computer	1 ~ 2
0601B	Female	67	smartphone, tablet & computer	3
0602A	Male	66	smartphone & computer	1.5
0607A	Male	69	smartphone, tablet & computer	2 ~ 3
0608A	Female	68	smartphone, tablet & computer	play when having time
0609A	Female	53	smartphone, tablet & notebook	0.5
0609B	Female	71	smartphone & computer	1.5
0609C	Female	68	smartphone, tablet & computer	3 ~ 5
0610A	Female	61	smartphone, tablet & computer	3
0610B	Female	57	smartphone, tablet & computer	8
0614A	Female	57	smartphone & computer	5
0615A	Female	68	smartphone	15 ~ 16
0615B	Female	65	smartphone, tablet & computer	using when awake
0616A	Female	68	smartphone, tablet & computer	3 ~ 4
0622A	Male	67	smartphone	3 ~ 4

2.2 Procedures

The in-depth interview was conducted through a semi-structured interview. Ethical approval was obtained from the research ethics committee of the author’s institute (202005HS071). The researcher adopted a flexible questioning approach with the aim of guiding the respondents to provide comprehensive answers, including (1) initial reasons why they were exposed to technology, (2) motivation and needs for participation (or not participating) in digital learning, (3) intentions to and attitude toward digital learning, and (4) adaptation status of older people when participating (or not participating) in digital learning.

Questions on motivations and need for participating (or not participating) in digital learning included: "What do you think about participating in digital learning? ", " Do you usually engage in digital learning? How often? What kind of behavior do you engage in when you do? What are your reasons for participating (or not participating) in digital learning?" and " What are the advantages or disadvantages of participating in digital learning? " These questions were used as the starting questions for the interview, and through the respondents’ answers, we asked further questions regarding the reasons and thoughts behind these motivations.

The questions on the adaptation status of older people when participating (or not participating) in digital learning will be "In what ways do you believe your involvement in digital learning has impacted your life, either positively or negatively?” and " Have you encountered any problems or difficulties when participating in digital learning in the past?" these questions were used to explore the respondents’ experiences and adaptations in the past. The interviews were recorded in order to have complete picture for the interview.

2.3 Coding framework and data analysis

The current coding system involving precursors of exposure to technology (Q1), acceptance factors and barrier factors to digital learning (Q2), intention to perform digital learning (Q3), perceived behavioral controls (Q4), and digital learning behaviors (Q5) were adopted for investigating older adults’ learning. Accordingly, the current coding framework as adopted to explore the research aims.

3.1 Inter-rater consistency

In order to investigate the inter-rater consistency, four interviews were coded with 78 meaningful units. Two well- trained coders with education or psychology backgrounds were assigned for the coding, and the inter-rater kappa reliability was above 0.7 (k = 0.84; p < 0.001), which was considered excellent consistency according to Fleiss, Levin (34). Finally, all the 20 interviews were divided into 368 units.

3.2 Precursors of exposure to technology

According to Fig. 1, it compiles older adults’ precursors of exposure to technology. As can be seen in Fig. 1, social influence (counts: 33) and perceived usefulness (counts: 11) are two major precursors for older adults, leading to participating in digital learning. It suggests that older adults would like to try digital learning when their family or friends encourage them to do so or they themselves perceive technology as useful.

3.3 Acceptance and barrier factors to digital learning

Table 2 involves older adults’ acceptance factors and barriers to digital learning. The results revealed five acceptance factors and six barriers to digital learning. Regarding older adults’ acceptance factors of digital learning, perceived ease of use (PEU), perceived usefulness (PU), perceived enjoyment (PE), social influence (SI), and facilitating conditions (FC) were identified. In addition, participation in digital learning was hindered by barrier factors like lack of learning opportunities (LLO), privacy protection (PP), unenjoyment (UE), equipment issue (EI), perceived harmful for health (PHH), and personal Factors (PF).

Table 2

*Acceptance and barrier factors regarding older adults’ digital learning*
	Theme	Subthemes	Examples
Acceptance factor	Perceived ease of use (PEU)	Users find it easy to use	Well, the interface, the interface is easy to use. (0607A-07)
	Perceived usefulness (PU)	Able to reach the goal	many functions of mobile phones, you can also use this as a watch, replacing some...Some have a lot of functions…(0607A-03)
		Convenient	It's also faster like you don't have to go to the bank, you can handle it directly using online banking. (0602A-11)
		Bonus	That kind of payment has a lot of discounts, a lot of accumulated points, feedback, or something. (0525A-18,19)
	Perceived enjoyment (PE)	Relax and relieve tension	During the covid-19, you can adjust your body and mind even indoors, relieve the pressure, your anxiety, and then, then, the restriction that you can't go out. (0609B-26)
	Social influence (SI)	To connect with young people in the family	Like Pokémon, during the time we are catching Pokémon, my daughter and my husband may catch it, oh this is a Pokemon ~ oh ~ then we catch it (0614A-16)
		To interact with friends	I think it's brain games, being with people... And interacting with people through this. (0607A-20,21)
		Trends	I will make it as one of my goals for learning, because it is in line with the future world. because I think this will be the trend in the future. (0614A-11)
	Facilitating conditions (FC)	Stores/Institutions	When I was in the PX mart, the cashier was very nice, he helped me to do it and gave a little demo. (0609B-02)
		Courses	I took a class and learn with regards to the use of mobile phones. (0519A-01)
		Relatives and friends	If there is a problem, my son will solve it for me. (0525A-01)
Barrier factors	Lack of learning opportunities (LLO)	Lack of learning resources	Because my children are not by my side, my husband is a little bit worse than me, so I explore technology by myself. (0616A-01)
	Privacy protection (PP)	Doubts about personal data security	Personal data is stolen, you need to be able to distinguish right from wrong, correct or incorrect, and you must always pass on the information you receive. (0608A-18,19)
	Unenjoyment (UE)	Not fun	I just made a quick glance on that game, I think it is very boring. (0609B-19)
	Equipment issue (EI)	Difficult interface & function for older adults	I didn’t know where to click at the beginning. (0609A-07,09)
	Equipment issue (EI)	Unstable signal/ not unlimited	It’s just that sometimes the internet doesn’t work, you have to wait a minute or two for it to try again. (0519B-07)
	Perceived harmful to health (PHH)	Eye damage	What I feel right now is that we are all staring at the screen, which will be very difficult for our eyes since we are aging... (0622A-11)
		Psychological addiction	You will not be aware of the time, and you will keep playing without knowing what time it is. (0610A-10)
		Time-consuming	The first one is a waste of time because I don't think it's helpful to me. (0601A-02)
	Personal Factors (PF)	Insufficient willingness	My child forced me to use it, I used it for a while and then became lazy again and bring back my old habits. (0525A-12,13)
	Personal Factors (PF)	No time	Because I feel that my time seems to be a bit insufficient, and I have no extra time for it. (0608A-15)

3.4 Intention to perform digital learning

As can be seen in Fig. 1, the elderly’s acceptance factors and barrier factors result in three types of intention to participating digital learning: intention to use (ITU), no intention to use (NIU), and paradoxical hesitation towards technology (PHT). PHT was identified as the coexistence of acceptance factors and barrier factors.

3.5 Perceived behavioral controls and digital learning behaviors

Table 3 illustrates perceived behavioral controls that interacted together with individuals’ intentions to their actual digital learning behaviors. Table 4 contains three types of senior digital learning behaviors. As can be seen in Fig. 1, the digital learning process from intentions to behaviors were shown. Together with ITU and PHT, life benefits (LB), keep up with the times (KWT), build a habit and trust (BHT), pass time (PT), and external situational needs (ESN) emerged during older adults’ digital learning and tend to be more related to as Tech-native Learners (TNL) or Tech-novice learners (TnL). However, with NIU, lack of willingness and interest (LWI) and worry and doubts (WAD) were found to has relation with tech-rejector learners (TRL).

Table 3

*Older learners perceived behavioral controls regarding digital learning*
Reasons and experiences	Definitions	Examples
Life benefits (LB)	It is beneficial in our lives or makes our lives more convenient.	I realize that after playing this game, the knowledge or insights inside it, or some things it says may be useful to me. (0610A-06)
Keep up with the times (KWT)	Helping individuals to grow and catch up with this generation	This is also the trend of the generation, you have to follow it, and technology is advancing, you have to follow it to know that the current technology is advancing.(0610B-18)
Build a habit and trust (BHT)	Individuals build a habit and establish a routine through the use of technology.	When I wake up in the morning, I check the weather first, then wait for the bus, after that, I check my email and line and wait for the bus to arrive, and check for my documents. (0601B-10)
Pass time (PT)	Individual use technology to fill in ample time or when they get bored.	I just take it out to play when I'm bored.... Hey, sometimes I just use play as a way of leisure and entertainment like that. (0609C-14)
External situational needs (ESN)	Work or study requires the use of technology	I work in a nurse aide, so I pay more attention to (digital games), which ones are more suitable... (0601B-11)
Lack of willingness and interest (LWI)	Loss of interest and willingness due to laziness or physical and mental factors	I'm not interested in that, because I think it will take a lot of time, and then it hurts my eyesight and it takes a lot of time. (0615A-01,02)
Worry and doubts (WAD)	Worry about the negative impact of technology	I think digital games may be easier to get addicted to, you will not know what time it is, you keep on playing it, and without knowing what time it is, it is easy to get addicted to it. (0610A-10)

Table 4

*Three types of senior digital learning behaviors*
Types of digital learners	Definitions and Characteristics	Examples
Tech-native Learners (TNL)	Learners who have a strong technological proficiency seamlessly integrate technology into their learning, using it adeptly to solve problems they encounter along the way.	I frequently use an app called Foodie because I enjoy making snacks. Additionally, I use Telegram for communication purposes. Another useful platform I utilize is trip.com, which helps me with travel planning. Lastly, I use a graphics software called Sketch. (0517A-16)
Tech-novice learners (TnL)	Learners who are forced and pressured to choose and make use of technology; use technology as a replacement of their traditional life, rather than an augmentation which improves their traditional life; only operates the simple basic functions of technology.	I find it challenging to keep track of my transactions and sometimes struggle to remember whether I have made a payment or not. (0609C-03)
Tech-rejector learners (TRL)	Learners who are unwilling to use technology in their learning process.	I'm not interested in that, because I think that it takes a lot of time, and then it hurts my eyes,..., (0615A-01,02,04)

3.6 Sequences and process of older adults’ digital learning

Figure 1 shows sequences and process of older adults’ digital learning in the current framework. The framework represents precursors, acceptance and barrier factors to digital learning, intentions, perceived behavioral controls, and actual learning behaviors. Figure 1 reveals older adults’ digital learning process by showing social influence led the elderly to exposure to technology a total of 33 times. Additionally, we could observe 29 situations in which older adults perceived usefulness after they were exposed to technology, thus leading the intention to use technology. In terms of older adult learners having an intention to use technology, they also exhibited a positive attitude toward technology. They regarded that technology makes lives more convenient by giving additional rewards and benefits (17 times). They felt a higher degree of behavioral control and finally were identified as tech-native learners (8 times).

In contrast, we could identify 16 situations in which they perceived technology harmful for health and 14 situations where they rejected digital technique due to personal factors such insufficient willingness and time after they were exposed to technology, thus, leading to no intention to use it. Furthermore, when older adults do not have an intention to use technology, they also exhibited a negative attitude toward it. A total of 11 situations were classified as the lack of willingness and interest and 3 were identified as worry and doubts toward technology. Thus, they felt a little degree of behavioral controls and this finally were identified as tech-rejector learners (10 times).

Last but not least, the current results revealed a paradoxical hesitation among older adults towards technology when they participate in digital learning. During this special process, both acceptance and barrier factors were identified and mixed all together leading to PHT. With PHT, little behavioral controls were found.

4.1 Social influence as older adults’ major precursor of exposure to digital learning

The current findings revealed that social influence is the major mechanism behind why older adults would be initiated the exposure to technology or to learn using digital devices, which advances the previous research and contributes a unique finding especially targeting the elderly population. According to our interviews, one of the interviewees mentioned that I'm involved in digital learning due to the suggestions from my friends and family(0517A-06). In addition, participants even engaged in digital learning because of conformity. For example, I noticed that those people around me were actively involved in digital learning, which inspired me to do the same(0519A-07) & (0607A-21).

Our findings are also consistent with previous research. For example, research investigated the relationships between social influence and the acceptance of technology for older adults, indicating that the role of social influence would lead to technology adoption (e.g., 35, 36–38). Also, Lüders and Gjevjon (20) conducted a series of qualitative research and found that the reasons of older adults’ intention of exposure to technology are related to social influence or social interaction. In addition, van den Hoogen, Ijsselsteijn (39) suggested that social interaction boosts acceptance toward technology.

According to Wang and Hwang (40), they examined the satisfaction of the basic psychological needs as older adults perform daily activities. They indicated that the elderly perceived greater psychological satisfaction when accompanied by others, regardless of who their companions are. It was suggested that older adults emphasized their social connections and would perceive greater psychological satisfactions when doing daily activities.

Accordingly, of all factors, the role of social influence is especially essential to understanding the mechanisms behind how to encourage older people to get started with digital learning.

4.2 Barriers (such as LLO, PP, and UE) are crucial factors in shed light on why older adults tend to be unwilling to learn with the use of technology.

The current research, except investigation of the acceptance toward digital learning, contributes to provide the older adults’ barriers hindering from learning with technology, which advance previous research and created a unified theory especially targeting for the elderly. Parallel to our findings, Di Giacomo, Ranieri (25) discussed the nature of technophobia and examined characteristics of non-digital older individuals. They indicated that these older adults experience computer-related anxiety, affecting their daily lives through low adherence to digital life.

Our theory is consistent with previous research results. For example, Jung, Walden (19) investigated the mechanisms why older adults are unwillingness to use Facebook. They found and indicated several factors include privacy issues, unwilling to spend time getting familiar with Facebook, and limited site skills. In addition, Damodaran, Olphert (41) suggested that older adults’ barriers to digital learning include the absence of adequate support, lack of confidence in using ICT’s, and memory problems with understanding technical jargon. Also, Betts, Hill (42) mentioned that one of the obstacles prevents older adults from using technology is the concern of information security. Parallelly, Knowles and Hanson (43) indicated that older adults frequently demonstrated distrust when using digital technology.

4.3 Older adults’ paradoxical hesitation towards participating in digital learning

The current research findings revealed that older adults experience paradoxical/contradictory intention to participate in digital learning. This finding is paralleled with the “repetitive tension” mentioned by Zhu (44). In the research of Zhu (44), the elderly initially had a positive attitude towards digital learning. They perceived digital learning offered more opportunities compared with traditional learning. Nevertheless, when they were exposed to digital devices, they become nervous and anxious as they encountered difficulties. Therefore, when older adults learn with the use of technology or learn how to use technology, their perceived contradictory or tension between negative emotions (such as being nervous) and motivating forces (such as the willingness to do or being forced to keep up with the times) went through their entire digital learning process. Also, Rohner, Hengl (45) indicated that older participants in their research regarded themselves as a handicap in the process of learning due to getting old. However, these older people felt interested in technology. Even though they are willing to use technology, they perceived pressure and forced to use it.

This paradoxical intention may also have something to do with contradictory motivation co-existing with older adults’ inner mind. According to Melenhorst, Rogers (31), older adults’ acceptance of technology is related to two kinds of motivation: direct positive motivation and direct negative motivation. Direct positive motivation refers to benefits and an absence of costs. Benefits define the advantages aroused out of the usage of technology, as well as absence of costs refers to the drawbacks that are decreased through using technology. However, direct negative motivation has something to do with costs and an absence of benefits. In this regard, costs involve the disadvantages when using technological devices, and absence of benefits indicate the advantages of reducing using technological devices. In the same way, Wang, Chen (46) also indicated that older adults, compared with younger people, tend to be more conservative about the technology adoption, and that they often need more assistance and scaffolding when using them. In this research, Wang, Chen (46) suggested some paradoxical factors emerging all together to affect older adults behaviors. For example, motivation for using technology, inclusive of maintaining a positive self-image and self-compensation. Conversely, negative perception and experiences regarding digital devises were all interactively found to result in older adults’ intention and behaviors toward technology.

Besides, older people emphasized more and are worried about privacy issues when they use technology, thus leading to a more paradoxical/contradictory situation. Gatto and Tak (47) indicated that older adults also enjoyed digital activities and the functions and added value that technology provide and assist with learning. However, the fear and worry about privacy and security would prevent them from using technology. Also, older adults experience more obstacles hindering them from continuing to perform digital learning.

4.4 Older adults’ outcomes or behavioral types when digital learning: TNL, TnL, and TRL

In the current research, three types of senior digital learners were found: TNL, TnL, and TRL. The results were suggested that digital divide (48, 49) still exist. TNL were coded in the current research based on three characteristics: (1) digital learning as autonomous choice; (2) using technology as augments to enhance their original life; (3) using high-level functions of technology to assist daily needs. The findings are consistent with previous research findings.

For example, Sayago, Forbes (50) indicated that digital learning of the elderly was driven by their needs from everyday life. Accordingly, they may use technologies for their lives such as e-mail and Skype. In the research of Tsai, Shillair (51), it was suggested that using digital devices made the elderly feel connected to their friends and families, as well as keep up with times. They used digital devices for checking weather, devotional studies, maintaining sports as well as health monitoring. Pihlainen, Ehlers (52) also found that the elderly participated in digital learning since they would like to achieve independence in their everyday life by obtaining digital skills.

Quan-Haase, Martin (53) also proposed the characteristics of “digital seniors,” which identify people who are active and senior digital users. According to their findings, digital seniors can create hybrid practices and recreate existing practices with digital manners. They combine traditional habits and life with new one emerging from digital use and regard digital as a tool that enhances traditional life. For digital seniors, agency is central for them to adoption or non-adoption of digital technology. They are equipped with ability to choose technology wisely and flexibly under what situations and for what purposes. Also, digital seniors do not perceive anxious nor being forced to use technology; instead, they make choices totally from their freedom and autonomy, based on their own preferences, convenience of use, and affordability.

Also, according to the research findings of Hutto, Bell (18), it was suggested that the elderly’s attitude toward digital technique matter when it comes to their life adaptation. Technology should be as augments of daily life but replacements. They live with technology and use it better if they regard digital technology as augments instead of as replacements and changes of their original life.

4.5 Limitations, future directions, and conclusions

Several limitations exist within the current work. First, the participants are not representative and the results should not be generalized due to the small sample size. Future work should investigate with a larger sample size conducting quantitative approach. Second, this work may have sampling bias. It may be challenging to recruit or even invite participants who have never heard about digital learning. Also, those who had no access to get to know the information about digital learning may not have participated in the current research. Future research or educators should invite more rural seniors to try digital learning and test whether learning with technology is also adaptive and useful for them. Finally, in this study, all interviews were collected only with audio recording; therefore, to make future research rigorous, multiple measures or recording methods could be adopted (e.g., videotaping, or self-reported questionnaires).

To develop a theory entirely tailored made for the elderly during digital learning, the current research is dedicated to extending the existing framework and findings but focusing on the senior target and under the circumstances of digital learning by adding barrier factors and highlighting the target specific characteristics - paradoxical hesitation towards technology (PHT). Furthermore, the current study induced, coded, and unified all elements that emerge throughout the whole older adults’ digital learning process from findings mechanisms why they are exposed to technology, identifying both acceptance and barrier factors, exploring the target specific PHT and to classifying three types of older adults’ digital learning. Therefore, we believe that this study contributes a reference for elderly digital learning field and serving the accumulated number of older adult learners.

Ethics approval and consent to participate

All experiment conducted in this study received approval from the Research Ethics Committee of National Taiwan Normal University. Additionally, informed consent was obtained from all participants prior to their involvement in the research.

Consent for publication

Not applicable.

Availability of data and materials

The dataset of the present study is available upon request from the corresponding author (Ya-Ling Wang, email: [email protected]).

Competing interests

There are no competing interests to declare.

Funding

This work was supported by the National Science and Technology Council, Taiwan [MOST 111-2423-H-003-002-MY4].

Authors' contributions

Ya-Ling Wang was the sole author of this paper and contributed to research design, data collection, data analysis, and write up.

Acknowledgements

The author expresses gratitude to all participants for their valuable contribution to this study through their participation.

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No competing interests reported.

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Technophilia or technophobia: The unified model of the paradox of older adults’ digital learning

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Abstract

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1. Background

1.1 Motivation and acceptance of digital learning for older adult learners

1.2 Barriers hindering the elderly from digital learning

1.3 Approach-avoidance conflict in digital learning for the elderly: paradoxical hesitation towards technology

1.4 Older adults digital learning outcomes and behaviors

1.5 Current study

2 Materials and Methods

2.1 Participants

2.2 Procedures

2.3 Coding framework and data analysis

3 Results

3.1 Inter-rater consistency

3.2 Precursors of exposure to technology

3.3 Acceptance and barrier factors to digital learning

3.4 Intention to perform digital learning

3.5 Perceived behavioral controls and digital learning behaviors

3.6 Sequences and process of older adults’ digital learning

4 Discussions

4.1 Social influence as older adults’ major precursor of exposure to digital learning

4.3 Older adults’ paradoxical hesitation towards participating in digital learning

4.4 Older adults’ outcomes or behavioral types when digital learning: TNL, TnL, and TRL

4.5 Limitations, future directions, and conclusions

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References

Additional Declarations

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