Empowering families in hands-on science programs

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Meaningful Teens. Braided Seeds. Knowledge of Child Development — Parents who understand how children grow and develop are able to provide an environment where children can reach their potential.

Parental Resilience — The ability to effectively manage all types of challenges that occur in life is crucial for parents. Parents who are able to manage stress and function well are less likely to direct anger and frustration toward their children. Social Connections — Having a sense of connectedness with constructive, supportive persons and with the community provides encouragement and assistance in meeting the daily challenges of raising a family.

Support for Parents — Parents who are able to identify and access resources to meet their basic needs including food, clothing, and shelter ensure the health and well-being of their children.

Complicated principles are taught in a simple way, but they are not merely taught—the children are encouraged to think about them carefully on their own over an extended period. But science and technology are part of everyday life. The Great East Japan Earthquake struck in Miyagi Prefecture, where Tohoku University is situated, was among the regions that sustained major damage, and places for local children to learn were also lost. Revitalizing the centers of science and technology education and raising children to take their places in the science and technology society of the future would help bring energy to Miyagi.

At that time, there was an offer of financial support from the government of Qatar, and events such as hands-on science lessons and education seminars started under the name of Tohoku University Qatar Science Campus.

Tohoku University Science Campus Hall. Under this initiative, the teaching staff and students of the School of Engineering acted as lecturers, teaching lessons centered on experiments to children in the sixth year of elementary school within Sendai, with one of the aims being to serve as a practical way of providing intellectual services to the local community. Under the management of the Innovation Plaza, it started afresh under the name of the Tohoku University Science Campus.

The initiative to convey the fun of science is beginning to bear real fruit. We ask companies to provide lessons that do not end up just as an experience of making something or doing an experiment, but that give children an opportunity to learn scientific principles and to think for themselves through trial and error. This could be due to an overall increased interest in AI in the public. For both years, the majority of guardians that came with the students were mothers, grandmothers, aunts and older sisters.

To test whether higher dosage of engagement led to higher learning gains, parent survey responses were compared from — Fig. The programs in , and were 5 weeks long with families spending between 6—10 h in hands-on STEM projects. The program in was the AI technology competition for families extending for 15 weeks across the year, while the AI competition in was 10 weeks in length. All the programs appeared to attract parents who wanted their children to learn more about Science and Technology, however the AI competitions attracted families with a higher level of pre-self-efficacy.

This was expected as participation in a global AI competition requires a threshold level of interest, curiosity and self-efficacy. There were paired pre- and post-survey respondents in and 31 in The significant reduction in post-survey completion in was due to participants not being required to complete post-surveys.

The Sign Test was used to test for significant differences between paired pre- and post-survey responses. Significant gains were seen in and This result was not surprising, given their decision to enroll their child into such a program.

For the season coaches,compared to the in , registered to implement the program locally. Following the training, coaches engaged with almost 3rd-8th grade students and parents, meeting weekly for 2 h over a 10 week period. Coaches were mostly educators who were proficient in science, technology, and math, but less so in coding, engineering, and electronics. The competition element of the program provided the usual combination of pros and cons: time-based deadline that motivated families to persist and submit their prototypes, excitement of competing at a global level counterbalanced by stress, frustration, impatience, and forced deliberation.

These three clusters Fig. Only about 20 mentors from industry were able to connect with families due to challenges in geographical matching. Most of the families were supported by their site educator, who in turn was trained and supported by the Technovation team. Students tested their understanding of concepts through selected response questions on the curriculum platform. If they selected the wrong answer, they were prompted to try again.

For both seasons, there was a decline in the number of participants who completed quizzes after the first lesson, from in Lesson 1 to in Lesson 2 for Season 1, and from in Lesson 1 to in Lesson 2 Fig. Nearly half of participants who completed lessons did not take the quiz. Those who continued to take the quiz were able to improve their ability to correctly answer questions as the lessons progressed, as shown by the increasing percentage of correct first tries, verifying that comprehension increases with higher dosage and program participation.

For each of the two seasons, at least three judges gave an impartial assessment of the quality of the AI-prototype based on a rubric that targeted the desired outcomes of the program. Based on the analysis of data, changes were made to improve the curriculum and rubric. Four of the core categories did not change: problem definition, Use of AI, Innovation or Uniqueness of the solution, and Project Execution.

A new section was added around Responsible Invention. A significant decline of 5. This may be due to ethical constraints newly added to the season, which may have introduced a product specification that not all teams were able to meet adequately.

However, improvements to the curriculum appeared to result in a trend of better execution of the project, and improved likelihood of a successful invention and product. After the program, 34 interviews with families in the US, Cameroon, and Bolivia were conducted to gain a better understanding of why families signed up for the program, what they were expecting from the experience and what enabled them to finish it successfully. Universal themes across the three countries and socio-economic groups were that parents wanted their children to work on something that they were passionate about, leading them to happiness and success; the AI program was a way for parents to learn more about their children as well as themselves; and parents appreciated increasing their own problem-solving and technological abilities at the same time as their child.

For all, the biggest barrier to participation was time. Keeping these findings in mind the length of the program was reduced from 15 to 10 weeks in , and more emphasis was placed on improving the AI-focused curriculum modules so that families could still be successful in developing working AI-prototypes within the compressed timeframe.

For , six interviews were conducted with families and mentors from India, Pakistan and Cambodia. Themes that emerged were that the compressed curriculum without the hands-on design challenges was less engaging for the families. Mentors and parents recommended more case studies, examples of AI being used to tackle local problems and flexibility in choosing topics and content according to interest and skill level.

Comparing 2 years of implementation of a global AI competition engaging under-resourced families revealed a few insights and areas of further exploration that are relevant to organizations and groups interested in AI literacy, upskilling and helping all communities develop future-ready skills.

Table 4 lists the programmatic and curricular differences between the and programs. A logistical lesson was that recruitment of industry mentors over summer is not effective or efficient due to different vacation schedules. Key features of successful mentoring were: having a strong community partner geographically close to an industry partner and mentors having prior experience with mentorship.

Community partner liaisons also needed to be flexible and good communicators. Based on these findings, one program improvement could be to use the pre-survey attributes to direct volunteers to specific volunteering opportunities to maximize engagement and positive impact. Figures 5 , 7 and 8 illustrate that the families did make gains in content knowledge, creativity and persistence, although the gains were smaller in comparison to The difference in learning gains across the 2 years could be due to higher economic development in the cohort as the program implementation stipend from Technovation was significantly reduced —resulting in a higher baseline and lower net gains in creativity and persistence.

The question-responsible invention module was a first step in helping participants reflect on various consequences of their invention for different user groups. Improved content would enable more participants to better understand and apply the value-sensitive design principles, leading to an improved prototype. The following are key features of a successful AI-education program model for under-resourced communities, combining best practices from literature and the experience of running an AI-entrepreneurship program for 20, participants from under-resourced communities, across 17 countries for 2 years:.

Beyond content, towards purpose—with the continued rise in interest in AI, and online learning due to COVID, the emphasis for education programs and platforms needs to move beyond just content knowledge. Interviews with participants show that learners need to see the value and application of knowledge to real-world problems, while building their own sense of purpose and self-efficacy as problem solvers, entrepreneurs and leaders.

Making learning engaging—following online programming tutorials is not engaging for novices. Strategies to improve retention include providing a variety of project-based learning lessons, starting from hands-on, unplugged activities and then moving onto software projects. Feedback frequency needs to be higher as well, at least weekly [ 38 ]. This can be accomplished by recruiting and training mentors, and matching them with the families.

The geographical barriers can be overcome by encouraging virtual mentorship.