Keywords

1 Introduction

It is considered that individuals will experience a “growing aging era” in the near future, wherein the proportion of older adults will be over 20%. In particular, Japan is a “hyper-aging society,” which an aging population of 26.7% (2015), and the average number of births is 1.45 (2015) [8, 32]. The hyper-aging society seems to be growing [32], and the lifestyle and working environment should be improved in order to ensure the phenomenon of “aging well” in the society. However, due to the advancement of information and communication technologies (ICT), we have many solutions to support the aging society in order to facilitate “aging well,” which is a phenomenon to promote and maintain one’s active status physically, mentally, and cognitively.

One of the solutions is to promote elder people’s “sense of purpose” in their life. Sense of purpose seems to be one of the strong factors that allow elderly people to maintain their health and well-being [42]. A “sense of purpose,” which refers to a motivation to do something, such as contributing to the social development, seems to be an important factor [42]. Designing and building a learning environment for the elderly in order to support their working would be useful to enhance their sense of purpose. In fact, 65.9% of the elderly over 65 years of age want to continue working beyond 70 years of age [32]. Robson et al. (2006) suggested the criteria for successful aging at workplace using factor analysis [36]. The results showed that five elements are important to ensure active aging at workplace: adaptability and health, positive relationships, occupational growth, personal security, and continued focus and achievement of personal goals [36]. One of these elements, “occupational growth,” is negatively correlated with age. In order to support their will to continue working, suitable learning environments for the elderly should be provided. This study aimed to investigate the effective designs of the learning support system for the elderly by reviewing previous studies. We selected the papers indexed in the ERIC (Education Resources Information Center: https://eric.ed.gov) under the “peer-reviewed” condition, published between 1977 and 2017. We retrieved seven peer-reviewed journal papers using the keyword “elder people” and 30 papers using the keyword “aging well.” However, we eliminated five papers because these papers were not related to education and learning research. Additionally, we reviewed the journal “Educational Gerontology” to obtain hints about the learning environment design with ICT. In the latter part of the study, we reviewed the relationship between the cognitive aspect and ICT use for elderly. In this paper, major findings from the previous research are introduced and the learning design perspectives for elderly are described.

2 Educational Aspects of Aging and ICT

In the era of information technology, learning about ICT is important for the elderly. Marston et al. (2016) pointed out that a digital divide exists between generations; however, social networking has been recently becoming popular among the elderly [28]. Hernández-Encuentra et al. (2009) indicated that attitude, experience of use, and perceived benefits of ICT use play an important role in ensuring the enhancement of autonomy and confidence in the elderly [24]. However, several points should be considered when designing learning environments for the elderly in terms of the characteristics of the elderly, such as memorization. For example, Gatti et al. (2017) pointed out three viewpoints of learning difficulty experienced by the elderly: declining perceptual and motor skills, cognition, and psychosocial sense [20]. This section introduces the design perspectives of learning environment for the elderly.

2.1 Motivation and Perception of ICT Use

Motivation is a useful perspective when designing learning environment for all age groups. If researchers and developers understand the motivation of the elderly people to learn about ICT, it might be possible to design and develop an environment that enhances their motivation. Motivation to learn about ICT includes an active mind and social participation. In order to learn about ICT use, memorizing and attention should be trained [21]. Hasan and Linger (2016) investigated elderly people’s perception of meaningful use of computer in aged care settings [22]. The results showed the seven categories: connection, self-worth/esteem and personal development, productivity, occupation, self-sufficiency, being in control, and enjoyment [22]. Ng (2008) investigated the factors of elderly people’s motivation to learn computer skills using a grounded theory approach [33]. The results showed that social involvement, such as social support and relationships, enhance their motivation [33]. Purdie and Boulton-Lewin (2003) conducted a survey about the important needs and barriers to learning information technology among 160 older adults [34]. The results showed that older people wanted to learn about ICT related to transportation, health management, and safety. The strongest barrier was physical disabilities, and the weakest barrier was socialization [34].

Considering the above, there are many factors that affect elderly people’s motivation to learn but socialization such as building social relationships and involvement are strong motivational factors that are useful for designing a learning environment.

2.2 Learning Environment Design from Face-to-Face Settings About ICT Use

Perspectives of face-to-face instructions and observation seem to be useful to design learning environments for the elderly. Boulton-Lewis (2010) suggested seven viewpoints to support learning for the elderly: Self-confidence, the use of coping strategies, maintaining cognitive function and knowledge, health management, keeping up with technology development, maintaining social relationships, and encouraging wisdom [7].

Based on data from 420 elderly people, Sayago et al. (2013) suggested that designing an environment for ICT learning requires a connection with daily life (information learning settings), collaborative learning, and appropriate cognitive learning strategies [37].

Martin (1999) reviewed previous studies on skill training for the elderly and suggested the following implementation guidelines for elderly training: promoting active communication, reflection, positive feedback, and use of “I” statements, which recognizes skill training as “my” issue [29].

Ferreira et al. (2015) conducted a comparative research (ICT use group vs. Passive ICT group) to investigate the effects of ICT training on perception and behaviors [18]. The results indicated that elderly people in the ICT use group tended to engage in social behaviors and had a positive self-perception of physical environments and quality of life.

Findsen (2015) pointed out that the problems in elderly people’s learning such as the decline of cognition and less flexibility should overcome assumption and the importance of learning environments that enhance social contextualized and situate learning [19].

Gatti et al. (2017) developed a lecture for tablet use in order to enhance empowerment, information integration, and autonomy. The results indicated that the designed lecture was effective on the enhancement of elderly peoples’ self-efficacy [20].

In the context of environmental sustainability, elderly people’s role is important in intergenerational interaction to maintain a practical community [17]. The findings seem to suggest that providing a role to the elderly in the learning community could be effective on elderly’s learning ability.

As stated in the previous research, not only social perspective but also the perception of “self” is an important factor to enhance elderly learning.

2.3 Interface Design of Learning Environment for Elderly

In Human-Computer Interaction (HCI) research, many studies about usability and accessibility for the elderly have been conducted. Recently, this research area has been discussing the methods to investigate the need for designing a digitally-extended environment based on tablets [1]. Lin et al. (2014) investigated the usability and accessibility of touch-screen interface in the context of online newspaper reading [26]. Their research indicated that page-flipping, zoom-in and out, and icon graphics can lead to misunderstanding and difficulty to control for the elderly people. Affordance should be considered for the design of software interfaces for the elderly [43]. Wong (2013) indicated that mobile user interface and socio-economic factors such as age, health condition, and prior product experience can strongly influence the perception of usability [43].

Arfaa and Wang (2014) also suggested similar difficulties faced by the elderly when using social media [2]. Zajicek (2001) indicated that voice help interface and showing the difference between usable and unusable functions is useful for older adults in the context of web browser development [46]. Calvo et al. (2017) investigated the effects of computer-based cognitive learning tool “concept map” for elderly, wherein the effects of a computer-based concept mapping tool for the enhancement of critical thinking were examined [9]. The results revealed that the effects were recognized by elderly people but it depended on their attribution data such as the perception of computer use difficulty, knowledge level, and age [9]. Usability, such as expanding objects and double-click, plays an important role in the perception of ease to use this system.

Learning environments for the elderly should be developed by integrating HCI and education and learning research, reviewing the above. One HCI research suggested that gameful interactive design could be useful for elderly people [31]. Considering the above, not only input support function such as voice input support but also supporting function to use cognitive strategies is required in the design of learning environment.

3 Cognitive and Neural Aspects of Aging and Learning

3.1 ICT and Aging

To develop an effective design of a learning support system for the elderly, we need to understand the cognitive and neural changes with age. In this section, we review peer-reviewed journal papers on cognitive and neural aspects of learning and aging from selected four major gerontology or gerontological psychology journals: “Psychology and Aging,” “Gerontologist,” “Gerontology,” and “Journals of Gerontology Series B-Psychological Sciences.”

First, we investigated the studies on ICT and elderly people. We found two peer-reviewed journal papers using the keywords “ICT” and “older adults.” Since the keywords “ICT” and “elder people” did not yield any search results, we used the keyword “older adults.” One paper was a review of the methods for understating the use of aging-in-place ICT [13], and the other reported an investigation of elderly people’s use of ICTs and the preventive or promotive factors of sustainable use [15]. Damodaran et al. [15] surveyed 323 older ICT users (aged ≥50 years) by conducting questionnaire surveys and interviews. They reported that many elderly people are enthusiastic, competent, and confident users of ICTs. Nevertheless, the elderly people reported several difficulties regarding ICT use, such as technological complexity and change, age-related capability changes, and a lack of learning and support mechanisms. Frequently-reported difficulties in remembering things (e.g., passwords, or all the steps in a process) might be related to their cognitive ability such as declined working memory. Although it may deviate from our main topic, we must pay attention to the physical aspects to develop an effective design of a learning support system for the elderly people. For instance, arthritis of the hands might lead to the elder people facing difficulties in using a mouse or a keyboard.

3.2 Aging and Learning

Using the keywords “learning” and “older adults,” we retrieved 146 papers published between 1992 and 2017 in the four selected journals. Figure 1 shows the number of papers in each five-year period, except for the 1992–1995 and 2016–2017 periods. The steady increase in the number of studies on “learning” and “older adults” can be seen during these decades. It may reflect the “hyper-aging society” and requirements of the present situation as mentioned before.

Fig. 1.
figure 1

Number of journal papers retrieved using the keywords “learning” and “older adults” in each five-year period from 1992 to 2017, except for the 1992–1995 and 2016–2017 periods

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Here we introduce selected cognitive research works that focused on learning and aging from the 146 papers. First, we review papers that investigated age difference in the cognitive functions and its brain mechanism. Second, training effects on cognitive and meta-cognitive functions are introduced.

3.3 Age Differences in Cognition

Cognitive functioning changes with aging, and it affects learning [25]. There are numerous research papers on the age differences in the cognitive functions, and its scope is very wide. In this section, we selected some research papers that may relate to learning with ICT among elderly people.

Aging affects the fundamental level of cognition such as visual processing [10, 14], memory [6, 30, 39], category learning [3, 41], and higher level of cognitive functions, such as strategy [16, 40], skill acquisition [23], and sentence reading [27, 38]. These cognitive functions play an essential role in the learning process, not only with ICT. We introduce these studies below.

Visual Processing

Costello et al. [14] reported age-related decline in change detection in visual processing. They suggested that this negative effect of aging is largely due to processing speed, although some strategy-level effects may also contribute. On the contrary, Campbell et al. [10] did not report simple decline of cognitive function with aging. Their results indicated different visual learning patterns between younger and older adults. Younger adults demonstrated better performance for the attended stimuli than they did for the unattended stimuli. However, older adults showed no difference between the attended and the unattended stimuli. In other words, the older adults continued their performance with the unattended stimuli. Campbell et al. implied that older adults may actually know more than younger adults about the world around them, including how seemingly irrelevant events co-occur.

Memory

Bopp and Verharghen [6] performed a meta-analysis of the effects of age on verbal short-term memory and verbal working memory span tasks. Their main findings are as follows.

  1. a.

    Age differences were found in all verbal span tasks.

  2. b.

    Working memory span is more age sensitive than short-term memory span.

  3. c.

    Span of younger adults and span of older adults are linearly related.

Toth et al. [39] examined how aging and prior knowledge affect memory and metamemory. The results showed that prior knowledge increased recollection in both younger and older adults. However, while younger adults showed benefits of prior knowledge on accuracy of prediction of their ability to remember information at a later time, older adults did not. Toth et al. suggested that prior knowledge acted as a double-edged sword for older adults, enhancing recollection but undermining the accuracy of memory predictions.

McGillvray et al. [30] investigated whether younger and older adults’ metacognitive judgments and memory are affected by one’s level of curiosity and interest. In their study, memory performance on trivia questions did not show difference between younger and older adults. Their analysis indicates that interest had a unique increasing relationship with older adults’, but not younger adults’, memory performance after a week. They proposed that these results suggest that subjective interest may enhance older adults’ memory.

Category Learning

Wahlheim et al. [41] investigated age difference in category learning. They found that performance was higher among younger than among older adults. This suggests that older adults were impaired in their ability to learn the correct rule or remember exemplar-label associations. Badham et al. [3] examined three hypotheses on how older adults represent categories, (a) rule complexity: categories were represented exclusively with rules (b) rule-specific: categories could be represented either by rules or by similarity (c) clustering: similarity was mainly used. Rule-complexity and rule-specificity were not supported by the performance data. Rather, computational modeling of the data indicated that the older adults utilized fewer conceptual clusters of items in memory than did young adults.

Strategy

Touron and Hertzog [40] examined how age differences in strategy selection are related to associative learning deficits and metacognitive variables, including memory ability confidence. In their study, older adults showed an aversion to using the memory retrieval strategy. This avoidance of the retrieval strategy correlated to lower confidence in their general ability to use the memory retrieval strategy. A research by Davis and Weisbeck [16] used wayfinding strategy, which refers to finding one’s way in the environment. They examined the types of self-reported search strategies and cues that older adults use to find their way in a virtual maze. In their results, some of the strategies differed among age groups and over time. The oldest age group was less likely to use strategies such as triangulation and distance strategies, and the older participants less used geometric cues. Davis and Weisbeck pointed out that further studies need to determine how cognitive factors affect wayfinding strategies and performance.

Skill Acquisition

Head et al. [23] examined the impact of age-related differences in regional cerebral volumes and cognitive resources on acquisition of a cognitive skill. They employed the Tower of Hanoi puzzle and the Wisconsin Card Sorting test as cognitive skill tasks. In the early stage of skill acquisition for both tasks, speed and efficiency were associated with age, prefrontal cortex volume, and working memory. However, if hypertensive participants were excluded, the effect of prefrontal shrinkage on executive aspects of performance was no longer significant, but the effect of working memory remained.

Sentence Processing

In a sentence processing research, Stine-Morrow et al. [38] investigated age differences in the allocation of effort when reading text for either recall accuracy or efficiency. When active monitoring of their memory was required, older people showed less efficient allocation than did young people for reading time and memory performance. This suggests that active memory monitoring might be resource-consuming for older learners. Liu et al. [27] used a self-regulated reading paradigm to investigate age differences in the effect of information richness (i.e., sentence elaboration) and costs of switching between texts (i.e., time delay) on selection of sources and study time allocation. The effect of switching cost was larger for older adults than younger in the high switch cost condition. There was no age difference in reading strategy; that is, readers selected less information-rich text first and then moved to more information-rich texts.

3.4 Training Effects on Cognitive and Metacognitive Functions

As shown above, many studies reported decline in the working memory of older adults [6, 23, 38, 41]. Bailey et al. [5] examined whether working memory performance improves after training individuals to use effective encoding strategies. After training, both younger and older adults used effective strategies more frequently and had improvements in working memory performance. Age-related working memory deficit was not greatly affected; however, the effectiveness of training did not transfer to the other cognitive tasks. Metacognitive training, which refers self-testing and efficient study allocation, for older adults’ memory was also investigated [4]. Compared to the control group, the trained group showed better performance. From a different point of view that engaging in learning new skills improves episodic memory in older adults, Chan et al. [11] investigated whether sustained training of using a tablet computer and associated software improve episodic memory. In their results, older adults who were trained to use tablet computer showed greater improvements in episodic memory and processing speed but did not differ in mental control or visuospatial processing.

3.5 Summary

In this section, we briefly review the previous studies about “ICT” and “older adults” in terms of age difference with respect to cognitive functions and its brain mechanism and the effects of training on cognitive and meta-cognitive functions. Table 1 shows the summary of the results of the papers on age difference. Most of the studies on age differences reported decline in cognitive function with aging, and this was related to deficits of memory, especially working memory. However, some studies not only reported decline but also some improvement. Research papers on cognitive [5, 11] and metacognitive training [4] suggest that training improves cognitive and metacognitive functions but improvements did not transfer to other cognitive domains. From these studies, we suggest that for designing an effective learning support system for the elderly people, we need to consider memory decline and support system to encourage the use of effective cognitive strategies.

Table 1. Summary of the results of papers on age differences. The order of the papers corresponds with appearance order.
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4 Conclusion

This paper reviewed the previous studies on educational and cognitive perspectives of ICT use for the design of learning environments for the elderly. These studies have pointed out the challenges and barriers, such as decline in cognitive functions and memorization, faced by the elderly when learning about ICT. On the other hand, the perception of the “self,” building social relationships, and playing roles in the community could enhance the learning motivation and performance of the elderly. For example, collaborative learning environments that involve visualization of participants’ role and contribution can be an effective learning environment for the elderly. The findings of the Computer-Supported Collaborative Learning (CSCL) research contributes to the design of learning environment for the elderly, such as scaffolding for reflection [35] and visualization [44, 45].

Future research should focus on a concrete design of collaborative learning environments for the elderly and its evaluation. Education and learning research focuses on the criteria for aging well. Assessment methods for the improvement of learning environments for the elderly should be based on cognitive psychology, and measure of aging well should be based on developmental psychology [42]. Chapman (2005) suggested the viewpoints to understand the facet of aging well, which include “negotiation of the co-construction and reconstruction of multiple selves in an ongoing, open-ended process of meaning-making amid later-life events and transitions” [12]. These viewpoints are concerned with the self and social perspective and should be considered for evaluation.