This chapter looks at the use of the internet for online learning. Respondents were asked about online learning activities for educational, professional, or private purposes which they undertook in the previous three months.
Note: The data presented in this release relates to individuals aged 16 years and over who used the internet in the three months prior to completing the survey.
Over half (53%) of internet users aged 75 years and over had downloaded or installed software or apps in the three months prior to completing the survey, while one-third (33%) had changed settings of a software app or device (such as adjusting language, colours, contrast, text size, toolbars/menu). Similarly, 36% had edited photos, videos, or audio files, using software/apps including freeware such as CapCut, iMovie, Picsart, etc. sorting, filtering, using functions, creating charts, etc. for uploading to their social media networks, or for other private use.
Analysis by sex/age group shows that males were more than four times more likely to write code in a programming language. Almost one-fifth (18%) of males had this ICT skill compared with 4% of females. Younger males aged 16 to 29 years were most likely to have the high level coding in a programming language (31%).
For performing basic Excel functions, males were more likely to have this ICT skill – 63% of males compared with 48% of females. The disparity was greater for performing more advanced features of spreadsheet software, with males (46%) more than twice as likely than females (22%) to have this ICT skill/knowledge.
Females aged 75 years and over were marginally more likely than males of a similar age to do an online course (such as audio-visual materials, online learning software, electronic textbooks) – one in twelve (8%) females aged 75 years or over compared with 6% of males in this age group.
Similarly, more than one in five (22%) females in this older age group were using online learning material and resources to aid their learning (including audio-visual materials, online learning software, electronic textbooks, etc.), compared with 15% of males in this age cohort.
Analysis by deprivation quintile shows that the take-up of online learning whether it be doing a formal online training course or using online learning material to aid one’s learning, does increase with the level of affluence of the area in which one resides.
More than one-third (35%) of internet users residing in very affluent areas were doing an online course of some form in the three months prior to interview compared with over one in five residing in disadvantaged/very disadvantaged areas.
Online learning material was used by over half (54%) of people living in very affluent areas compared with 46% of internet users in disadvantaged/very disadvantaged areas.
Communicating online with educators/instructors using audio or video online tools such as Zoom, MS Teams, Google Classroom, Seesaw, Edmodo, etc. was most prevalent in households with children at 40% compared with 27% of people in households with no children.
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