Thursday, January 29, 2026
Wednesday, January 28, 2026
My 18-year Weight Management Records from 2007-05-28 to 2026-01-28 (by Calorie Restriction, i.e. Dietary Energy Restriction):
My 18-year Weight Management Records from 2007-05-28 to 2026-01-28 (by Calorie Restriction, i.e. Dietary Energy Restriction):
Note: According to the Singapore Health Promotion Board, a Healthy BMI is greater than18.5 and less than 23.0. A BMI less than 18.5 would mean that the individual is at risk of nutrition deficiency diseases and osteoporosis.
A BMI equal or greater than 23.0 would mean that the individual is at risk of obesity-related diseases. (Ref: DD-Md2022J28)
As of 2026-01-28,
Note: ### indicates BMI = 23 or > 23
Total number of Monthly Weight monitored was 224 (100%)
The no. of times my healthy BMI between 18.5 and 22.9 was 219 (97.767%)
The no. of times my unhealthy BMI equal or more than 23.000 was 5 (2.253%)
=======================
2007
2007-05-28 morning, my weight = 65.0 kg, BMI = 23.588###
2007-06-28 morning, my weight = 61.0 kg, BMI = 22.136
2007-07-28 morning, my weight = 59.0 kg, BMI = 21.410
2007-08-28 morning, my weight = 58.7 kg, BMI = 21.302
2007-09-28 morning, my weight = 57.5 kg, BMI = 20.866
2007-10-28 morning, my weight = 57.5 kg, BMI = 20.866
2007-11-28 morning, my weight = 56.2 kg, BMI = 20.394
2007-12-28 morning, my weight = 55.5 kg, BMI = 20.140
2008
2008-01-28 morning, my weight = 54.8 kg, BMI = 19.886
2008-02-28 morning, my weight = 54.8 kg, BMI = 19.886
2008-03-28 morning, my weight = 54.5 kg, BMI = 19.777
2008-04-28 morning, my weight = 54.4 kg, BMI = 19.741
2008-05-28 morning, my weight = 54.1 kg, BMI = 19.632
2008-06-28 morning, my weight = 54.6 kg, BMI = 19.814
2008-07-28 morning, my weight = 54.5 kg, BMI = 19.777
2008-08-28 morning, my weight = 54.3 kg, BMI = 19.705
2008-09-28 morning, my weight = 54.9 kg, BMI = 19.923
2008-10-28 morning, my weight = 55.3 kg, BMI = 20.068
2008-11-28 morning, my weight = 54.5 kg, BMI = 19.777
2008-12-28 morning, my weight = 55.6 kg, BMI = 20.177
2009
2009-01-28 morning, my weight = 54.8 kg, BMI = 19.886
2009-02-28 morning, my weight = 55.9 kg, BMI = 20.285
2009-03-28 morning, my weight = 54.8 kg, BMI = 19.886
2009-04-28 morning, my weight = 55.3 kg, BMI = 20.068
2009-05-28 morning, my weight = 55.4 kg, BMI = 20.104.
2009-06-28 morning, my weight = 55.2 kg, BMI = 20.031
2009-07-28 morning, my weight = 55.1 kg, BMI = 19.995
2009-08-28 morning, my weight = 55.2 kg, BMI = 20.031
2009-09-28 morning, my weight = 56.3 kg, BMI = 20.431
2009-10-28 morning, my weight = 55.8 kg, BMI = 20.249
2009-11-28 morning, my weight = 56.2 kg, BMI = 20.394
2009-12-28 morning, my weight = 56.1 kg, BMI = 20.358
2010
2010-01-28 morning, my weight = 55.6 kg, BMI = 20.177
2010-02-28 morning, my weight = 56.5 kg, BMI = 20.503
2010-03-28 morning, my weight = 56.4 kg, BMI = 20.467
2010-04-28 morning, my weight = 55.7 kg, BMI = 20.213
2010-05-28 morning, my weight = 55.1 kg, BMI = 19.995
2010-06-28 morning, my weight = 56.4 kg, BMI = 20.467
2010-07-28 morning, my weight = 55.5 kg, BMI = 20.140
2010-08-28 morning, my weight = 55.8 kg, BMI = 20.249
2010-09-28 morning, my weight = 55.8 kg, BMI = 20.249
2010-10-28 morning, my weight = 55.4 kg, BMI = 20.104
2010-11-28 morning, my weight = 55.6 kg, BMI = 20.177
2010-12-28 morning, my weight = 55.5 kg, BMI = 20.140
2011
2011-01-28 morning, my weight = 55.4 kg, BMI = 20.104
2011-02-28 morning, my weight = 56.5 kg, BMI = 20.503
2011-03-28 morning, my weight = 55.6 kg, BMI = 20.177
2011-04-28 morning, my weight = 55.7 kg, BMI = 20.213
2011-05-28 morning, my weight = 55.6 kg, BMI = 20.177
2011-06-28 morning, my weight = 56.3 kg, BMI = 20.431
2011-07-28 morning, my weight = 56.5 kg, BMI = 20.503
2011-08-28 morning, my weight = 56.9 kg, BMI = 20.649
2011-09-28 morning, my weight = 56.2 kg, BMI = 20.394
2011-10-28 morning, my weight = 56.8 kg, BMI = 20.613
2011-11-28 morning, my weight = 59.0 kg, BMI = 21.410
2011-12-28 morning, my weight = 60.3 kg, BMI = 21.882
2012
2012-01-28 morning, my weight = 61.5 kg, BMI = 22.318
2012-02-28 morning, my weight = 62.7 kg, BMI = 22.753
2012-03-28 morning, my weight = 62.5 kg, BMI = 22.681
2012-04-28 morning, my weight = 61.3 kg, BMI = 22.246
2012-05-28 morning, my weight = 60.7 kg, BMI = 22.028
2012-06-28 morning, my weight = 60.6 kg, BMI = 21.992
2012-07-28 morning, my weight = 61.2 kg, BMI = 22.209
2012-08-28 morning, my weight = 60.8 kg, BMI = 22.064
2012-09-28 morning, my weight = 61.5 kg, BMI = 22.318**
2012-10-28 morning, my weight = 62.3 kg, BMI = 22.608
2012-11-28 morning, my weight = 63.4 kg, BMI = 23.008###
2012-12-28 morning, my weight = 62.9 kg, BMI = 22.826
2013
2013-01-28 morning, my weight = 63.0 kg, BMI = 22.863
2013-02-28 morning, my weight = 62.1 kg, BMI = 22.536
2013-03-28 morning, my weight = 61.5 kg, BMI = 22.318
2013-04-28 morning, my weight = 63.1 kg, BMI = 22.899****
2013-05-28 morning, my weight = 62.3 kg, BMI = 22.608
2013-06-28 morning, my weight = 62.2 kg, BMI = 22.572
2013-07-28 morning, my weight = 62.4 kg, BMI = 22.645
2013-08-28 morning, my weight = 62.6 kg BMI = 22.717
2013-09-28 morning, my weight = 62.4 kg BMI = 22.645**
2013-10-28 morning, my weight = 62.3 kg BMI = 22.609
2013-11-28 morning, my weight = 63.1 kg BMI = 22.899
2013-12-28 morning, my weight = 64.4 kg BMI = 23.371###
2014
2014-01-28 morning, my weight = 63.6 kg, BMI = 23.080###
2014-02-28 morning, my weight = 63.3 kg, BMI = 22.971
2014-03-28 morning, my weight = 62.7 kg, BMI = 22.753
2014-04-28 morning, my weight = 62.7 kg, BMI = 22.753
2014-05-28 morning, my weight = 62.9 kg, BMI = 22.826
2014-06-28 morning, my weight = 63.1 kg BMI = 22.899
2014-07-28 morning, my weight = 62.7 kg, BMI = 22.753
2014-08-28 morning, my weight = 62.2 kg, BMI = 22.572
2014-09-28 morning, my weight = 61.2 kg, BMI = 22.209
2014-10-28 morning, my weight = 61.4 kg, BMI = 22.282
2014-11-28 morning, my weight = 60.2 kg, BMI = 21.846
2014-12-28 morning, my weight = 60.8 kg, BMI = 22.064
2015
2015-01-28 morning, my weight = 61.3 kg, BMI = 22.246
2015-02-28 morning, my weight = 61.8 kg, BMI = 22.427
2015-03-28 morning, my weight = 61.8 kg, BMI = 22.427
2015-04-28 morning, my weight = 62,5. kg, BMI = 22.681
2015-05-28 morning, my weight = 62.4 kg, BMI = 22.645
2015-06-28 morning, my weight = 63.6 kg, BMI = 23.080###
2015-07-28 morning, my weight = 62.3 kg BMI = 22.609
2015-08-28 morning, my weight = 62.2 kg, BMI = 22.572
2015-09-28 morning, my weight = 63.0 kg, BMI = 22.863
2015-10-28 morning, my weight = 63.2 kg, BMI = 22.935
2015-11-28 morning, my weight = 62.6 kg, BMI = 22.717
2015-12-28 morning, my weight = 62.3 kg BMI = 22.609
2016
2016-01-28 morning, my weight = 63.0 kg, BMI = 22.863
2016-02-28 morning, my weight = 62.8 kg, BMI = 22.790
2016-03-28 morning, my weight = 62.0 kg, BMI = 22.499
2016-04-28 morning, my weight = 62.0 kg, BMI = 22.499
2016-05-28 morning, my weight = 62.4 kg, BMI = 22.645
2016-06-28 morning, my weight = 62.1 kg, BMI = 22.536
2016-07-28 morning, my weight = 62.2 kg, BMI = 22.572
2016-08-28 morning, my weight = 62.6 kg, BMI = 22.717
2016-09-28 morning, my weight = 62.8 kg, BMI = 22.790
2016-10-28 morning, my weight = 62,5. kg, BMI = 22.681
2016-11-28 morning, my weight = 62.1 kg, BMI = 22.536
2016-12-28 morning, my weight = 62.3 kg, BMI = 22.608
2017
2017-01-28 morning, my weight = 62.9 kg, BMI = 22.826
2017-02-28 morning, my weight = 62.4 kg, BMI = 22.644
2017-03-28 morning, my weight = 62.8 kg, BMI = 22.789
2017-04-28 morning, my weight = 62.3 kg, BMI = 22.609
2017-05-28 morning, my weight = 62.2 kg, BMI = 22.572
2017-06-28 morning, my weight = 62.6 kg, BMI = 22.717
2017-07-28 morning, my weight = 62.4 kg, BMI = 22.645
2017-08-28 morning, my weight = 61.9 kg, BMI = 22.463
2017-09-28 morning, my weight = 62.0 kg, BMI = 22.499
2017-10-28 morning, my weight = 62.0 kg, BMI = 22.499
2017-11-28 morning, my weight = 61.5 kg, BMI = 22.318
2017-12-28 morning, my weight = 61.5 kg, BMI = 22.318
2018
My Weight 2018-01-28 0934 hr 61.0 kg BMI 22.136
My Weight 2018-02-28 0915 hr 60.7 kg BMI 22.027
My Weight 2018-03-28 0620 hr 61.0 kg BMI 22.136
My Weight 2018-04-28 1005 hr 61.7 kg BMI 22.390
My Weight 2018-05-28 0856 hr 60.5 kg BMI 21.955
My Weight 2018-06-28 0600 hr 61.4 kg BMI 22.281
My Weight 2018-07-28 0600 hr 62.2 kg BMI 22.572
My Weight 2018-08-28 0720 hr 61.4 kg BMI 22.281
My Weight 2018-09-28 0805 hr 62.1 kg BMI 22.535
My Weight 2018-10-28 0750 hr 61.3 kg BMI 22.24
My Weight 2018-11-28 1000 hr 61.5 kg BMI 22.318
My Weight 2018-12-28 0650 hr 62.5 kg BMI 22.681
2019
2019-01-28 at 1000 hr 60.9 kg BMI 22.100
2019-02-28 at 0946 hr 61.0 kg BMI 22.136
2019-03-28 at 0700 hr 62.4 kg BMI 22.644
2019-04-28 at 0828 hr 62.9 kg BMI 22.826
2019-05-28 at 0745 hr 62.4 kg BMI 22.826
2019-06-28 at 0650 hr 62.4 kg BMI 22.644
2019-07-28 at 0736 hr 62.8 kg BMI 22.789
2019-08-28 at 0629 hr 62.4 kg BMI 22.644
2019-09-28 at 0644 hr 61.9 kg BMI 22.463
2019-10-28 at 0740 hr 62.5 kg BMI 22.681
2019-11-28 at 0632 hr 62.8 kg BMI 22.789
2019-12-28 at 0726 hr 62.5 kg BMI 22.681
2020
My Weight 2020-01-28 0625 HR 62.6 kg BMI 22.717
My Weight 2020-02-28 0728 HR 62.3 kg BMI 22.608
My Weight 2020-03-28 0649 HR 61.4 kg BMI 22.281
My Weight 2020-04-28 0810 HR 62.0 kg BMI 22.499
My Weight 2020-05-28 0714 HR 62.3 kg BMI 22.608
My Weight 2020-06-28 0757 HR 60.2 kg BMI 21.846
My Weight 2020-07-28 0715 HR 61.6 kg BMI 22.354
My Weight 2020-08-28 0707 HR 61.1 kg BMI 22.173
My Weight 2020-09-28 0609 HR 60.8 kg BMI 22.064
My Weight 2020-10-28 0818 HR 60.7 kg BMI 22.027
My Weight 2020-11-28 0706 HR 60.9 kg BMI 22.100
My Weight 2020-12-28 0631 HR 60.5 kg BMI 21.955
2021
My Weight 2021-01-28 0638 HR 61.3 kg BMI 22.245
My Weight 2021-02-28 0741 HR 61.2 kg BMI 22.209
My Weight 2021-03-28 0659 HR 61.3 kg BMI 22.245
My Weight 2021-04-28 0659 HR 61.1 kg BMI 22.173
My Weight 2021-05-28 0618 HR 61.1 kg BMI 22.173
My Weight 2021-06-28 0604 HR 61.3 kg BMI 22.245
My Weight 2021-07-28 0642 HR 61.2 kg BMI 22.209
My Weight 2021-08-28 0653 HR 61.5 kg BMI 22.318
My Weight 2021-09-28 0618 HR 61.5 kg BMI 22.318
My Weight 2021-10-28 0549 HR 61.0 kg BMI 22.136
My Weight 2021-11-28 0630 HR 61.3 kg BMI 22.245
My Weight 2021-12-28 0528 HR 61.6 kg BMI 22.354
======================================
2022
My Weight 2022-01-28 0910 HR 61.1 kg BMI 22.173
My Weight 2022-02-28 0642 HR 61.2 kg BMI 22.209
My Weight 2022-03-28 0649 HR 61.4 kg BMI 22.281
My Weight 2022-04-28 0649 HR 61.4 kg BMI 22.281
My Weight 2022-05-28 0549 HR 61.0 kg BMI 22.136
My Weight 2022-06-28 0549 HR 61.0 kg BMI 22.136
My Weight 2022-07-28 0700 HR 60.6 kg BMI 21.991
My Weight 2022-08-28 0640 HR 61.3 kg BMI 22.245
My Weight 2022-09-28 0738 HR 61.7 kg BMI 22.390
My Weight 2022-10-28 0708 HR 61.5 kg BMI 22.318
My Weight 2022-11-28 0706 HR 60.9 kg BMI 22.100
My Weight 2022-12-28 0722 HR 61.1 kg BMI 22.173
========
2023
My Weight 2023-01-28 0537 HR 60.9 kg BMI 22.100
My Weight 2023-02-28 0515 HR 61.4 kg BMI 22.281
My Weight 2023-03-28 0606 HR 61.3 kg BMI 22.245
My Weight 2023-04-28 0738 HR 61.3 kg BMI 22.245
My Weight 2023-05-28 0721 HR 61.0 kg BMI 22.136
My Weight 2023-06-28 0641 HR 61.2 kg BMI 22.209
My Weight 2023-07-28 0700 HR 60.9 kg BMI 22.100
My Weight 2023-08-28 0655 HR 61.3 kg BMI 22.245
My Weight 2022-09-28 0738 HR 61.7 kg BMI 22.390
My Weight 2022-10-28 0708 HR 61.5 kg BMI 22.318
My Weight 2023-11-28 0612 HR 61.4 kg BMI 22.281
My Weight 2023-12-28 0734HR 61.3 kg BMI 22.245
========
2024
My Weight 2024-01-28 0734 HR 61.3 kg BMI 22.245
My Weight 2024-02-28 0510 HR 61.6 kg BMI 22.354
My Weight 2024-03-28 0642 HR 60.9 kg BMI 22.100
My Weight 2024-04-28 0721 HR 61.1 kg BMI 22.173
My Weight 2024-05-28 0537 HR 61.3 kg BMI 22.245
My Weight 2024-06-28 0651 HR 61.5 kg BMI 22.318
My Weight 2024-07-28 0612 HR 61.4 kg BMI 22.281
My Weight 2024-08-28 0747 HR 61.1 kg BMI 22.173
My Weight 2024-09-28 0640 HR 61.1 kg BMI 22.173
My Weight 2024-10-28 0546 HR 61.5 kg BMI 22.318
My Weight 2024-11-28 0706 HR 61.4 kg BMI 22.281
My Weight 2024-12-28 0649 HR 61.9 kg BMI 22.463
=======================================
2025
My Weight 2025-01-28 0625 HR 61.6 kg BMI 22.354
My Weight 2025-02-28 0742 HR 61.5 kg BMI 22.318
My Weight 2025-03-28 0640 HR 61.6 kg BMI 22.354
My Weight 2025-04-28 0734 HR 61.7 kg BMI 22.390
My Weight 2025-05-28 0738 HR 61.8 kg BMI 22.427
My Weight 2025-06-28 0606 HR 62.6 kg BMI 22.717
My Weight 2025-07-28 0757 HR 62.7 kg BMI 22.753
My Weight 2025-08-28 0546 HR 62.6 kg, BMI 22.717
My Weight 2025-09-28 0540 HR 62.2 kg BMI 22.572
My Weight 2025-10-28 0516 HR 62.4 kg BMI 22.644
My Weight 2025-11-28 0810 HR 62.1 kg BMI 22.535
My Weight 2025-12-28 0702 HR 62.2 kg BMI 22.572
=========================
2026
My Weight 2026-01-28 0733 HR 61.9 kg BMI 22.463
=========================
Note:
My current BMI is within the healthy range of 18.5 to 22.9.
For me, the range of healthy weight is 50.9786 kg (BMI = 18.5) to 63.10324 kg (BMI = 22.9).
People with BMI values of 23 kg/m2 (or 25 kg/m2 according to some sources) and above have been found to be at risk of developing heart disease and diabetes.
To be healthy, I must have a healthy weight.
Be as lean as possible without being underweight, as recommended by World Cancer Prevention Foundation, United Kingdom.
=================================
Note: On 2021-05-28, I removed the unimportant details of old records from My Weight Management Records.
=================================
Ref. WeightManagement
For students to feel seen, class size matters
https://www.straitstimes.com/opinion/for-students-to-feel-seen-class-size-matters
2026-01-28
By--- Jacqueline Ho is assistant professor of sociology at Singapore Management University. She studies education and inequality, with a focus on families’ experiences of education reform.
=====
In her best-selling memoir Totto-chan, Tetsuko Kuroyanagi tells the story of how she was expelled from school as a first-grader for her disruptive behaviour, but eventually flourished at Tomoe Gakuen, an alternative school.
Whereas she was distracted and disengaged in her old classroom, her new school gave each student the flexibility to begin the day with whatever learning activity most appealed to them. Totto-chan formed lifelong friendships at Tomoe, and even made a promise to her headmaster that she will return to teach there as an adult.
As someone who studies education, I can’t help but ask: What explains the contrast between her two experiences? The pedagogical philosophy of Tomoe’s headmaster is no doubt a core ingredient. But class size was likely also a key factor.
In the 2023 film adaptation of the book, there is a scene of Totto-chan’s old classroom that has exactly 40 students in it. At Tomoe, there are no more than 50 students in the entire school.
The policy question
What class size is appropriate? This is a perennial question in education policy. In Singapore, it has been debated in Parliament since at least the 1980s. It has once again surfaced amid concerns about teachers’ workloads.
The Ministry of Education’s (MOE) latest numbers show that our pupil-teacher ratio is 15.6 in primary schools and 12.7 in secondary schools. This is the total number of students enrolled across schools divided by the total number of teachers.
Our ratios are respectable by Organisation for Economic Cooperation and Development (OECD) standards. But low ratios may not translate to small classes.
In Primary 1 and 2, class sizes have been capped at 30 since 2006. Between Primary 3 and 6, average form class sizes range from 35 to 37. Between Secondary 1 and 4, they range from 33 to 35.
While class sizes may be smaller for higher-needs students and for specific subjects, we should focus on what the typical class size is for the modal student taking a core subject.
In the recent debates about teacher workload, class size reduction (CSR) has been absent from the menu of solutions offered by MOE. Instead, technology has been offered as an alternative. The recent introduction of AI-powered tools is intended to reduce workloads while customising teaching to individual learners’ needs.
Nonetheless, CSR continues to have strong advocates. Some teachers have voiced their opinion on social media, while parent group EveryChild.SG has proposed a plan to reduce class sizes in primary schools.
What the research says – and doesn’t say
Those arguing against it cite studies finding that class size is not actually that consequential when it comes to academic outcomes.
In recent years, MOE has repeatedly cited the OECD as an authority on this issue. The OECD’s reports argue that policymakers would see greater improvements in student outcomes if they invested in higher teacher quality rather than smaller class sizes.
Yet, given the methods used to arrive at this conclusion, our confidence in it might be misplaced.
The OECD reports are based on comparisons of all countries taking part in the Programme for International Student Assessment (PISA), and identify factors that are correlated with their PISA results. It turns out that teacher salary is highly correlated while class size is not.
Mr Andreas Schleicher, who directs the PISA studies, illustrates it this way in his 2013 TED talk: South Korea does well in PISA, despite its large classes. It also pays its teachers well. In contrast, Luxembourg performs below average, has small classes, and does not pay its teachers well. Thus, teacher quality trumps class sizes.
The problem is that we don’t have a complete picture of all the other factors that may be affecting PISA performance in these countries. Something else – for instance, its competitive educational culture – could be driving South Korea’s students to do well despite studying in large classes.
More On This Topic
Class sizes matter as teaching workload changes, say Singapore teachers
Inside Singapore’s education ‘arms race’: Stress, inequality and the push for change
The most rigorous studies use methods that help ensure that class size is the only factor that varies between comparison groups. This set-up gives researchers greater confidence that variation in outcomes is specifically due to variation in class sizes.
A prominent example is Project STAR (Student-Teacher Achievement Ratio), a large-scale, randomised controlled trial conducted in the 1980s in Tennessee that placed young students in classes of different sizes. Several studies using STAR data have found sizeable, positive effects of smaller classes.
Other studies using quasi-experimental methods have also found positive effects of varying sizes, while some have found no effect.
Overall, the literature does not argue that class size is an unimportant factor. Instead, it suggests that reducing class sizes may have a positive impact, under specific circumstances.
Beyond test scores
Even so, what we can learn from the literature is limited, because of its overwhelming focus on the impact of class sizes on academic outcomes.
By now, we can all agree that the goals of education stretch far beyond test scores. In this context, a country’s PISA performance cannot be the only barometer for evaluating the benefits of smaller classes.
Here are some other questions we should also be asking. Does class size influence whether students love learning, develop confidence, and learn to communicate their ideas?
If large classes mean that students and teachers cannot learn and teach in the ways they want to, is this what drives them towards the tuition industry or international schools?
Given that a third of our youth report poor mental health, and more students with special educational needs are enrolling in mainstream schools, how does class size impact teachers’ capacity to care for their students?
The research on these questions is limited. Nonetheless, we can make some educated guesses based on the data we have right before us: the lived experiences of teachers and families.
In my own research, I interview parents to learn about their experiences of the education system. The issue of class size regularly emerges, unprovoked. “The child feels lost,” as one mother said, explaining that children in large classes do not receive enough individual attention.
Her children say that their teachers are “very shouty”, which may be because classroom management is often more difficult in large classes.
Many parents say their parent-teacher meetings are 10-minute Zoom conversations, which simply cannot be very meaningful.
As a teacher myself, I know why this happens.
Last year, I had 15 students in my first semester and 41 the next. In the larger class, I sometimes had to deny students the opportunity to participate so we could end class on time.
More On This Topic
Still don’t get it? Here’s why teaching doesn’t always lead to learning
Is the focus on performance killing students’ curiosity?
My students wished they could write longer papers, yet I could not afford more time to grade these. By the end of the semester, I had got to know – as humans, not just as members of a class – a smaller fraction of the students than I had the previous semester.
To state the obvious, there is a mechanical relationship between the number of students a teacher has and the amount of attention they can give to each student.
Learning not just a cognitive process
Attention matters not simply because it enables students to get the academic support they need. It matters because relationships are foundational to a student’s learning and development.
Recent research in neuroscience, led by Professor Mary Helen Immordino-Yang, finds that learning is a deeply emotional process, not just a cognitive one. And students become more emotionally invested in their work if they can see its relevance to their lived experiences and identities.
This research provides evidence in support of what many teachers intuitively know: to get students engaged, make the material relevant to their lives. But to do this well, we first need to pay attention to our students and understand who they are.
Can we do this with technology, instead of smaller classes? That is a question for the teachers and students currently experimenting with AI-powered tools. But we would do well to heed sociologist Allison Pugh’s warning about a possible “depersonalisation crisis”. As more job functions are delegated to AI, Professor Pugh argues that we risk losing the “connective labour” that those in the caring professions provide – the seeing, the listening, the being with the other person that is as much a part of their value to society as is their technical function.
Connective labour is what the headmaster of Tomoe Gakuen provided when he listened to Totto-chan talk for four hours the first time he met her. “You’re really a good girl,” he told her at the end. This was news for Totto-chan, who had known herself to be a “bad girl” before that.
When we consider a change like reducing class sizes, we pay a lot more attention to the cost of the change than we do the costs of the status quo.
What is lost when a student is turned off from school because her teachers are “shouty”? Or when she misses out on chances to develop supportive relationships with adult mentors? What is lost when a burnt-out teacher misses a student’s distress signals, delaying the necessary interventions?
Thinking through these questions, we might ask how many Totto-chans sit quietly in our classrooms today, waiting for the time and attention that would allow them to flourish.
Jacqueline Ho is assistant professor of sociology at Singapore Management University. She studies education and inequality, with a focus on families’ experiences of education reform.
More On This Topic
Back to school? Let’s approach education in a new light – minus the glare
Don’t let AI change what it means to teach
蔡艳君博士：让乐龄人士跨越最后的数码鸿沟
https://www.zaobao.com.sg/forum/views/story20260128-8192044?utm_source=android-share&utm_medium=app
2026-01-28
作者是新加坡科技设计大学李光耀创新城市中心研究员。本评论基于“与人工智能同行的乐龄生活”（Ageing with AI）研究项目的相关发现
=====
从提取公积金到医疗预约，每一项基本的公共服务，都必须长期保留健全的非数码替代方案。这不应被视为过渡安排，而应成为数码社会的永久设计原则。一个睿智的国家明白：有时候，最聪明的技术，是一张真实的脸与耐心的交流。
76岁的陈先生居住在欧南园的租赁组屋。几十年来，他一直独立打理个人事务，用现金买咖啡、缴费，从不假手他人。如今，他默默站在一个数码自助服务机前，手里拿着一个他不理解的二维码，不敢按下任何按钮，因为他听说过朋友因诈骗而失去毕生积蓄。在一个因“智慧”而享誉全球的城市里，陈先生所面临的困境并非个例，尤其是在乐龄人士群体中 。
随着新加坡持续推进智慧国战略并加速人工智能（AI）的整合，国家正走到一个关键的矛盾点。一方面，我们正在建设一条承诺高效与便利的数码高速公路；另一方面，我们可能在无意中，将最脆弱的群体——尤其是70岁以上的乐龄人士——留在后面。我们近期对欧南园规划区213名55岁及以上的居民展开问卷调查显示，当下的数码鸿沟，早已不再是能否拥有智能手机的问题，而是在于谁拥有参与现代社会生活的能力与信心。如果我们不能从智慧国迈向睿智国（Wise Nation），就可能造成一个这样的社会——乐龄人士不仅在老去，更在我们的数码未来中逐渐隐形。
不仅仅是均值：沉默的鸿沟
新加坡人通常会从全国统计数据中获得一种心理上的安慰。我们看到60岁及以上人群的互联网普及率高达93%，便以为任务已经完成。然而，对全国社会经济弱势指数最高的欧南园深入研究，会为新加坡超级老龄化的未来揭示不同的景象。
在高楼林立的城市阴影之下，新加坡科技设计大学李光耀创新城市中心的一项研究发现，12%接受问卷调查的乐龄人士，完全没有任何数码设备。这一现实强调为什么必须避免并积极解决向“仅限数码”（digital only）倾斜的趋势。对效率的推进，促使我们关闭实体柜台，但对公平的追求，要求我们保持这些实体设施和服务的开放。从提取公积金到医疗预约，每一项基本的公共服务，都必须长期保留健全的非数码替代方案。这不应被视为过渡安排，而应成为数码社会的永久设计原则。正如城市为不同的出行者修建不同的出行通道，我们也必须在数码路径之外，持续建设“人的通道”。一个睿智的国家明白：有时候，最聪明的技术，是一张真实的脸与耐心的交流。
即便拥有智能手机，也不代表具备有意义的使用能力。全国数据显示，78%的乐龄人士使用线上银行或电子支付，但在欧南园的研究中，这一比率仅为26%。高达52个百分点的差距表明，更快的5G或更多应用，并不能自动跨越这最后的数码鸿沟。对于很大一部分新加坡乐龄人士，尤其是那些70岁及以上、收入较低、独居以及住在租赁组屋的群体来说，社会须要理解并尊重：他们是一群学得慢、经常忘记，以及在每一步骤都须要寻求确认的乐龄人士。
学习科技：信心的危机
问题的核心并非乐龄人士不愿学习。我们的研究显示，71%的研究对象从未接受过任何正式的数码或人工智能培训，在这些未受过培训的乐龄人士中，有40%明确表明愿意学习。
真正的问题在于：我们教导他们的方式或使用的语言可能并不正确。
我们往往将数码素养视为一种纯技术技能，就像学习修水龙头一样。于是我们开设“网络安全101”或“生成式人工智能入门”等传统课堂式课程。然而，对一个担心“点错一下就倾家荡产”的乐龄人士来说，科技更像是一个心理战场。如果我们要求他们在没有安全网的情况下，不断适应变化频繁的界面，我们并非赋权，而是在消耗他们。这也正是为何“数码优先”（digital first），在许多乐龄人士心中，变成“仅限数码”。系统的效率，可能转化为用户的焦虑。
此时，甘榜精神这种社区支持和邻里互助的价值观，恰恰可以成为数码普及的秘密武器。科技必须被日常化，成为社区对话的一部分。这意味着，应将更多资源投入到高度本地化、高度互动的介入方式，让乐龄人士在一个安全、联结、从容的环境中，通过反复尝试来学习。“数码大使”的角色应在乐龄人士的社区网络中成倍增加，赋能具备数码技能的乐龄人士去帮助同龄人。当陈先生的手机须要更新应用时，他可以走到最近的乐龄中心，找一位记得他名字，并会不厌其烦且毫无偏见地向他解释多次的数码大使。
这将使数码支持转化为日常的社区互动，显著降低焦虑与恐惧。
睿智国：在AI新前沿不落下任何人
来自欧南园的发现及时提醒我们，在推进数码化的过程中，不能假设所有人站在同一起跑线上。科技行业和政府必须在设计应用与技术时，与乐龄人士并肩同行。我们建议实施一项制度性的“乐龄用户验收测试”（Silver User Acceptance Testing）。任何面向公众的数码服务上线前，应由欧南园等老龄化社区中70岁以上的人群进行压力测试。如果乐龄群体无法顺利使用，代表这个产品尚未准备好发布。这也包括默认设置上的适老化：更大的字体、更高的对比度、更少的步骤、多语言选项，以及内置的可轻易撤销错误的容错设计，这些乐龄友好设计不应深藏在子菜单之中。
新加坡的叙事内核一直是“没有人会被落下”。当全球城市——从巴塞罗那到上海——同时应对快速老龄化与人工智能转型的挑战时，新加坡面临着重新兑现这一承诺的紧迫性。
欧南园的乐龄人士提醒我们，障碍从来不是年龄，而是设计与支持。他们愿意参与，但需要一个能与他们双向奔赴的系统。
我们的研究表明，具包容性的人工智能素养建设计划是必要的下一步。但这种素养必须建立在以人为本的设计原则之上。人工智能工具不能只是简单地空降到乐龄人士的生活中，他们也必须参与到设计过程中。
智慧国令人赞叹，而睿智国，则以尊严、联结与信任为核心，确保我们在迈向未来时，像陈先生这样的乐龄人士，始终与我们并肩同行。
======
作者是新加坡科技设计大学李光耀创新城市中心研究员。本评论基于“与人工智能同行的乐龄生活”（Ageing with AI）研究项目的相关发现
Helping Seniors Cross the Final Digital Divide*
Translated by ChatGPT
https://www.zaobao.com.sg/forum/views/story20260128-8192044?utm_source=android-share&utm_medium=app
2026-01-28
By Dr. Cai Yanjun
The author is a researcher at the Lee Kuan Yew Centre for Innovative Cities, Singapore University of Technology and Design. This commentary is based on findings from the research project “Ageing with AI”
=====
From CPF withdrawals to medical appointments, every essential public service must, over the long term, retain sound non-digital alternatives. This should not be seen as a transitional arrangement, but as a permanent design principle of a digital society. A wise nation understands that sometimes, the smartest technology is a real face and patient communication.
Seventy-six-year-old Mr Chen lives in a rental flat in Outram Park. For decades, he managed his personal affairs independently, buying coffee with cash and paying bills without relying on anyone else. Today, he stands silently in front of a digital self-service machine, holding a QR code he does not understand, afraid to press any button because he has heard of friends who lost their life savings to scams. In a city globally renowned for its “smartness”, the predicament Mr Chen faces is not an isolated case, especially among seniors.
As Singapore continues to advance its Smart Nation strategy and accelerates the integration of artificial intelligence (AI), the country has arrived at a critical point of tension. On one hand, we are building a digital expressway that promises efficiency and convenience; on the other, we may be inadvertently leaving behind the most vulnerable groups—especially seniors aged 70 and above. Our recent survey of 213 residents aged 55 and above in the Outram Park planning area shows that the current digital divide is no longer about whether one owns a smartphone, but about who has the ability and confidence to participate in modern social life. If we cannot move from a Smart Nation to a Wise Nation, we may end up with a society in which seniors are not only ageing, but also gradually becoming invisible in our digital future.
Not Just the Average: The Silent Divide
Singaporeans often derive psychological comfort from national statistics. When we see that internet penetration among those aged 60 and above is as high as 93%, we assume the task is complete. However, an in-depth study of Outram Park, which has one of the highest socio-economic disadvantage indices nationally, reveals a different picture of Singapore’s super-ageing future.
Beneath the shadows of towering buildings, a study by the Lee Kuan Yew Centre for Innovative Cities at the Singapore University of Technology and Design found that 12% of surveyed seniors had no digital devices at all. This reality underscores why we must avoid and actively address the drift toward “digital-only” models. The drive for efficiency pushes us to close physical service counters, but the pursuit of equity requires us to keep these physical facilities and services open. From CPF withdrawals to medical appointments, every essential public service must, over the long term, retain sound non-digital alternatives. This should not be seen as a transitional arrangement, but as a permanent design principle of a digital society. Just as cities build different pathways for different types of commuters, we must also continue to build “human pathways” alongside digital ones. A wise nation understands that sometimes, the smartest technology is a real face and patient communication.
Even owning a smartphone does not equate to having meaningful usage capability. National data shows that 78% of seniors use online banking or e-payments, but in the Outram Park study, this figure was only 26%. The 52-percentage-point gap demonstrates that faster 5G or more apps do not automatically bridge this final digital divide. For a large segment of Singapore’s seniors—especially those aged 70 and above, with lower incomes, living alone, and residing in rental flats—society needs to understand and respect that they are a group who learn slowly, forget easily, and need reassurance at every step.
Learning Technology: A Crisis of Confidence
At the core, the issue is not that seniors are unwilling to learn. Our research shows that 71% of respondents have never received any formal digital or AI training, and among these untrained seniors, 40% explicitly expressed a willingness to learn.
The real problem lies in how we teach them, or the language we use.
We often treat digital literacy as a purely technical skill, like learning to fix a leaky tap. Hence, we offer traditional classroom-style courses such as “Cybersecurity 101” or “Introduction to Generative AI”. However, for a senior who worries that “one wrong tap could wipe out everything”, technology feels more like a psychological battleground. If we require them to constantly adapt to frequently changing interfaces without a safety net, we are not empowering them—we are depleting them. This is also why “digital first” has, in the minds of many seniors, become “digital only”. System efficiency may translate into user anxiety.
Here, the values of kampong spirit—community support and neighbourly help—can become the secret weapon of digital inclusion. Technology must be normalised and become part of everyday community conversations. This means investing more resources into highly localised, highly interactive interventions, allowing seniors to learn through repeated practice in a safe, connected, and unhurried environment. The role of “digital ambassadors” should be multiplied within seniors’ community networks, empowering digitally skilled seniors to help their peers. When Mr Chen needs to update an app on his phone, he should be able to walk to the nearest senior activity centre and find a digital ambassador who knows his name and is willing to explain things patiently, repeatedly, and without prejudice.
This would transform digital support into everyday community interaction, significantly reducing anxiety and fear.
A Wise Nation: Leaving No One Behind at the New AI Frontier
The findings from Outram Park serve as a timely reminder that, in advancing digitalisation, we cannot assume everyone is starting from the same line. The technology industry and the government must walk alongside seniors in the design of applications and technologies. We propose implementing an institutionalised “Silver User Acceptance Testing”. Before any public-facing digital service is launched, it should be stress-tested by people aged 70 and above from ageing communities such as Outram Park. If seniors cannot use it smoothly, it means the product is not ready for release. This should also include age-friendly default settings: larger fonts, higher contrast, fewer steps, multilingual options, and built-in error-tolerant designs that allow mistakes to be easily undone. These senior-friendly designs should not be hidden deep within sub-menus.
Singapore’s core narrative has always been that “no one will be left behind”. As global cities—from Barcelona to Shanghai—grapple simultaneously with rapid ageing and AI transformation, Singapore faces an urgent need to re-deliver on this promise.
The seniors of Outram Park remind us that the barrier has never been age, but design and support. They are willing to participate, but they need a system that meets them halfway.
Our research shows that inclusive AI literacy programmes are the necessary next step. But such literacy must be built on human-centred design principles. AI tools cannot simply be parachuted into seniors’ lives; they must also be involved in the design process.
A Smart Nation inspires admiration, but a Wise Nation places dignity, connection, and trust at its core, ensuring that as we move toward the future, seniors like Mr Chen walk alongside us every step of the way.
The author is a researcher at the Lee Kuan Yew Centre for Innovative Cities, Singapore University of Technology and Design. This commentary is based on findings from the research project “Ageing with AI”.
Tuesday, January 27, 2026
Monday, January 26, 2026
Sunday, January 25, 2026
有和我一样喜欢独来独往的吗？
我今年六十岁，我突然发现，以前追着热闹跑。同学聚会，同事聚会，舞蹈队年会，有邀请必到。酒桌上相互恭维 ，称兄道弟，议论他人，现在回过头看看，...
https://m.toutiao.com/is/XQPIbzV7410/?share_token=190ef1dd-d19a-456d-9cf4-138ab2102abb
我今年六十岁，我突然发现，以前追着热闹跑。
同学聚会，同事聚会，舞蹈队年会，有邀请必到。
酒桌上相互恭维 ，称兄道弟，议论他人，现在回过头看看，那些都是无效的社交，不仅花钱，而且经常惹出烦恼。
最近一年我看透了人情世故，选择独来独往。
早上睡到自然醒，把家里收拾干净，出去买点菜，顺便扔了垃圾，回家坐在阳台上晒晒太阳，刷个手机，听个音乐，舒服的不得了。
而且我把微信上一年没聊过天的好友全部删除，不和任何人发早上好 等废话，留下几个亲戚好友，有事直接打微信电话，无事互不打扰。
我这种不合群，不代表我没有社交能力，只是我看透了人情世故，活得通透了。
60岁的人了，不愿意和他人接触太多，遇到没品位的人说话好呛人，与其生闲气，真的不如在家里，听听音乐，看看电视，练练毛笔字，做做饭，把家里打扫干干净净。
不与世俗争长短，这就是最好的生活，这就是通透的人生。
有和我一样喜欢独来独往的吗？
Saturday, January 24, 2026
What are the meanings of PP and 12x18 and 0.04 of the label of a plastic bag " PP12x18x0.04"?.
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The label
PP12x18x0.04 on a plastic bag refers to a specific type of transparent, rigid plastic bag often used for food packaging and display. Here is the breakdown of the meanings:
- PP (Material): Stands for Polypropylene. This is a, thermoplastic polymer known for being crystal clear, stiff, and having high heat resistance (up to 150°C). PP bags are generally used to enhance product display, such as for snacks, stationery, or apparel, and are stronger/less flexible than polyethylene (PE) bags.
- 12x18 (Size): Refers to the dimensions of the bag, typically 12 inches in width and 18 inches in height.
- 0.04 (Thickness): Refers to the thickness of the plastic film, measured in millimeters, as 0.04mm (or 40 microns). This is considered a standard, somewhat thin, but durable gauge for packaging, sometimes referred to as "04" or "40 microns".
Summary Table of Specifications
| Component | Meaning |
|---|---|
| Material | Polypropylene (Rigid & Clear) |
| Size | 12" x 18" (Width x Height) |
| Thickness | 0.04 mm (40 microns) |
Key Characteristics
- High Clarity: Offers superior transparency, making it ideal for displaying products.
- Moisture Barrier: Good at resisting moisture and vapor.
- Safety: Non-toxic, odorless, and suitable for food storage.
- Heat Resistance: Suitable for high-temperature sealing (up to 150°C).
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Missing: 12x18 0.04 label PP12x18x0.
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Missing: 12x18 0.04 label PP12x18x0.
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