Make Billions On The App Store - iPhone Dev Tools 101

•

5 likes•1,177 views

You might be motivated to get into iPhone development to make the next million dollar fart app, OR you might be like me and want to create great apps that you want to use. This is a hands-on introduction of the development tools used to build iPhone/iPad applications. I will cover Xcode, Interface Builder, iPhone Simulator, and Instruments, while building a small iPhone app demonstrating some of the capabilities of the platform. Prerequisites: some programming experience (not specifically Objective-C, I won't be focusing on syntactic sugar), and a desire to learn something new. Recommended: A Mac running the iPhone Xcode SDK will help if you want to follow along.

Technology

Make Billions on the
App Store
iPhone Development Tools 101
Podcamp Toronto 2010

Mark Pavlidis
mark@pavlidis.ca
http://twitter.com/mhp

Motivation

• >3 Billion downloads

• 25% Paid apps

Motivation

• >3 Billion downloads

• 25% Paid apps

• 50+ Million devices

Motivation

• >3 Billion downloads

• 25% Paid apps

• 50+ Million devices

• OR

Motivation

• >3 Billion downloads

• 25% Paid apps

• 50+ Million devices

• OR

• Build apps you want to use

RTFM

• Theres a doc for that!
• Help - Developer Documentation
• HIG (please please please)
• http://developer.apple.com/iphone/

Getting Started Books

Programming in Cocoa Programming For
Objective-C 2.0 Mac OS X
Stephen Kochan Aaron Hillegass

More Information

Mark Pavlidis
@mhp
mark@pavlidis.ca
http://spkr8.com/t/2114

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This study aimed to quantitatively synthesize the literature on gender differences in mental rotation ability in order to characterize the typical magnitude of the differences and their variations across studies. Since a series of studies led by Lubinski and Benbow has reported a critical role of spatial ability as a predictor of successful performance and developing expertise in science, technology, engineering, and mathematics (STEM) disciplines (e.g., Wai, Lubinski, Benbow, 2009), the value of spatial ability seems to be refreshed in STEM education more than ever. Since the early stages of research on spatial ability (Carroll, 1993; Eliot, 1987; Harris, 1978), studies on mental rotation ability, one sub-type of spatial ability, tend to provide consistent evidence for gender differences favoring males (Linn & Petersen, 1985; Voyer, Voyer, & Bryden, 1995). While the trend seems evident, the magnitude of the effect varies across studies with different populations and settings. In addition, the causes of the observed gender differences in mental rotation ability are not clarified yet (Masters, 1998; Moè, 2009). However, the literature suggests that the observed gender differences in mental rotation ability can be explained by at least five distinguishable factors: biological, strategic, experiential, affective, and performance. Among those five factors, we focused on performance factors to understand whether gender differences observed in scores are true or are due to the artifacts of the testing conditions. Specifically, we focused on the gender difference in three-dimensional mental rotation ability measured by The Purdue Spatial Visualization Tests: Visualization of Rotations (PSVT:R) (Guay, 1976), which has been prevalently used in STEM education for more than three decades. Addressed research questions are as follows: (a) What is the typical effect size of gender differences in mental rotation ability measured by the PSVT:R?; (b) To what extent do effect sizes vary across studies?; and (c) How do effect sizes differ by the types of the test, length of the test, time limits, administration modes, education levels, and participants’ majors? Fifty-four effect sizes obtained from 35 out of 153 studies that utilized PSVT:R were included in the meta-analysis. This study revealed that the PSVT:R has a significant gender difference favoring males with the weighted average of Cohen’s d=0.63, indicating a relatively large gender difference in spatial ability scores. The chi-square test of homogeneity (Q statistics) (Hedges, & Olkin, 1985) of effect sizes rejected the null hypothesis, implying that true effect sizes do vary across studies. Thus, additional analyses investigating moderating effects with random-effects models were warranted. Based on the descriptive results, testing conditions and sample and study characteristics were used as possible moderators in a multilevel model for a meta-analysis. Through this analysis, conclusions were made for each research question and followed by the discussion including implications in practice and suggestions for future research.

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The goals of this research study are to better understand the choices women in chemistry make with regards to career, to identify rewards and obstacles associated with available career choices in chemistry, and to compare graduate students’ perceptions of careers with the descriptions of women in those careers. Ten women graduate students in chemistry from two different institutions participated in a series of three interviews with the researcher. These interviews examined their chosen career path, their perceptions of available career options, their values about work-personal life balance, and their experiences as women in a graduate chemistry program. Women faculty members were also interviewed and asked to reflect on their career choices and provide insight into their lifestyle as academic chemists. Ten faculty members were interviewed, six from three different research-intensive universities and four from three different primarily undergraduate teaching institutions. All interviews were transcribed verbatim and subsequently analyzed using the qualitative methods of thematic analysis and the constant comparative method (Miles & Huberman, 1994). Preliminary analysis shows that women graduate students have negative perceptions of the research professor lifestyle at large universities. They feel there is little to no balance between work and personal life. Careers at primarily undergraduate teaching schools, at government labs, and in industry were viewed much more favorably. These findings add a depth of understanding to the numerous studies showing women’s tendency to favor academic careers at teaching institutions over research institutions (see Bentley & Adamson, 2003; Kuck, Marzabadi, Nolan, & Buckner, 2004; Kulis, Sicotte, & Collins, 2002; Sears, 2003). Women faculty members at large research institutions report deciding on their careers fairly early on in their graduate studies. They pursued this path even though they recognized the challenges associated with this career. Their primary motivation for continuing in their career was the intellectual freedom they experienced, followed by being able to work with students and help them develop into independent researchers. In contrast, the faculty members from smaller teaching institutions felt rewarded and fulfilled by teaching and working with students, rather than through chemical research. They valued the flexibility of their schedules and the ownership they had over their teaching and the research they did with undergraduates. The findings from this study offer suggestions for future interventions with graduate students, as well as faculty recruitment at research-intensive institutions. Women graduate students felt that women faculty in their department were not positive role models with respect to balancing a career with a family. They also did not see or value the intellectual freedom associated with this career or the rewards of working as an advisor to graduate students. Candid conversations or mentoring relationships outside of the advisor-advisee dynamic could shed insight into what life is really like as a faculty member at these institutions. Hiring and benefits packages at research institutions could also be modified with the addition of family-friendly benefits and policies, including maternity leave, on-site childcare, flexible tenure clocks, and clear departmental expectations for work schedules, to appeal to more women.

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Women have earned 40% of Ph.D.s in STEM disciplines in the U.S., yet their representation in academic STEM faculty and administrative positions has not wholly reflected this distribution (Hoffer, 2007; NSF, 2007): Women constitute on average only 20% of the faculty in fields related to science, technology, engineering and mathematics (NSF, 2000) a number which did not change proportionally to the degrees earned. In education fields in which the representation of women is traditionally much higher, an interesting conundrum exists: (1) Whereas men typically dominate technology fields, educational technology/instructional technology appears to be a field that has incorporated women more successfully than other STEM domains. (2) Technology education on the other side serves as a stark contrast as a K-12 oriented field that is noted for being male-dominated (Liedtke, 1995; Zuga, 1998). The fields of educational technology and technology education have arisen out of differing socio-historical and cultural contexts, which appear to have impacted the gender parity of each domain differently. This research study will explore the characteristics of graduate programs in Educational Technology/Instructional Technology as compared to Technology Education and explore the relationship of these characteristics to gender parity. Results of this study provide insight into strategies other fields might employ to increase participation of women. Through an evaluation of departmental characteristics such as highest degree offered and gender composition of faculty, we will present statistical data to demonstrate the gender parity/disparity in the academic domain in these two areas. Faculty gender composition can be a pivotal factor in a field’s ability to attract and retain a diverse student body due to role-model effect (Rask & Bailey, 2002). A content analysis of program descriptions and the prerequisite academic preparation and work experience to enter instructional technology versus technology education programs will be explored, as prerequisites (Klein, 2007) are another noted academic barrier to gender equity. This data will be contextualized in a historical analysis of the roots of these two similar, yet disparate, areas of study. While educational technology /instructional technology arose out of audio-visual education and school media, as well as programmed instruction, technology education arose out of the industrial arts tradition (Foster, 1994; O'Riley, 1996). Today, both fields are preoccupied with the concept of technological literacy and are dominated by the use of computer applications in a variety of contexts. As highly skilled educators are needed to model high level problem-solving and critical thinking skills through their use of technology, whether the field is technology education or educational technology, this analysis will offer insight into the cultural-historical perspectives that resulted in different gender parity, and recommend strategies for attracting women across technology-oriented domains.

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Make Billions On The App Store - iPhone Dev Tools 101

1. Make Billions on the App Store iPhone Development Tools 101 Podcamp Toronto 2010 Mark Pavlidis mark@pavlidis.ca http://twitter.com/mhp

2. Motivation

3. Motivation • >3 Billion downloads

4. Motivation • >3 Billion downloads • 25% Paid apps

5. Motivation • >3 Billion downloads • 25% Paid apps • 50+ Million devices

6. Motivation • >3 Billion downloads • 25% Paid apps • 50+ Million devices • OR

7. Motivation • >3 Billion downloads • 25% Paid apps • 50+ Million devices • OR • Build apps you want to use

8. iPhone SDK

9. iPhone SDK

10. iPhone SDK

11. iPhone SDK

12. iPhone SDK

13. iPhone SDK

14. iPhone SDK

15. iPhone SDK

16. Demo Time

17. Demo Time One more thing

18. RTFM • Theres a doc for that! • Help - Developer Documentation • HIG (please please please) • http://developer.apple.com/iphone/

19. RTFM • Theres a doc for that! • Help - Developer Documentation • HIG (please please please) • http://developer.apple.com/iphone/

20. Getting Started Books Programming in Cocoa Programming For Objective-C 2.0 Mac OS X Stephen Kochan Aaron Hillegass

21. Show me your code already!

22. More Information Mark Pavlidis @mhp mark@pavlidis.ca http://spkr8.com/t/2114

Editor's Notes

Shout out to Mark and Andrea watching on the video stream Thoughts are with you Been dev&#x2019;ing for iphone since the sdk dropped Claims to fame: - Toronto Traffic, et.al.: first traffic cams app - Shortcovers/Kobo - Twitter client in alpha
So maybe you here of this little thing called the App Store [click] > 3B downloads [click] 25% of those are paid apps averaging $3 [click] on > 50 Million devices worldwide [click] OR YOU CAN BE LIKE ME [click] and drop out of school and build apps you want to use (sorry dr. down)
So maybe you here of this little thing called the App Store [click] > 3B downloads [click] 25% of those are paid apps averaging $3 [click] on > 50 Million devices worldwide [click] OR YOU CAN BE LIKE ME [click] and drop out of school and build apps you want to use (sorry dr. down)
So maybe you here of this little thing called the App Store [click] > 3B downloads [click] 25% of those are paid apps averaging $3 [click] on > 50 Million devices worldwide [click] OR YOU CAN BE LIKE ME [click] and drop out of school and build apps you want to use (sorry dr. down)
So maybe you here of this little thing called the App Store [click] > 3B downloads [click] 25% of those are paid apps averaging $3 [click] on > 50 Million devices worldwide [click] OR YOU CAN BE LIKE ME [click] and drop out of school and build apps you want to use (sorry dr. down)
So maybe you here of this little thing called the App Store [click] > 3B downloads [click] 25% of those are paid apps averaging $3 [click] on > 50 Million devices worldwide [click] OR YOU CAN BE LIKE ME [click] and drop out of school and build apps you want to use (sorry dr. down)
Xcode Apple&#x2019;s IDE for building OS X, iPhone OS, Mac apps, iPhone Apps 3 SDK releases - Mac, iPhone, iPad app develpment (>2GB downloads) Interface Builder Prototyping and Implementation Tool - Graphically layout your interfaces - connect your interface to your code Iphone simulator Rapid prototyping and deployment iPhone API implementation on Intel hardware (not a hardware emulator) Instruments Performance analysis Tool Built with DTrace Object allocation, Memory management, file access, graphics - Versatile performance profiling - Powerful analysis - Fully understand the context of your data
Xcode Apple&#x2019;s IDE for building OS X, iPhone OS, Mac apps, iPhone Apps 3 SDK releases - Mac, iPhone, iPad app develpment (>2GB downloads) Interface Builder Prototyping and Implementation Tool - Graphically layout your interfaces - connect your interface to your code Iphone simulator Rapid prototyping and deployment iPhone API implementation on Intel hardware (not a hardware emulator) Instruments Performance analysis Tool Built with DTrace Object allocation, Memory management, file access, graphics - Versatile performance profiling - Powerful analysis - Fully understand the context of your data
Xcode Apple&#x2019;s IDE for building OS X, iPhone OS, Mac apps, iPhone Apps 3 SDK releases - Mac, iPhone, iPad app develpment (>2GB downloads) Interface Builder Prototyping and Implementation Tool - Graphically layout your interfaces - connect your interface to your code Iphone simulator Rapid prototyping and deployment iPhone API implementation on Intel hardware (not a hardware emulator) Instruments Performance analysis Tool Built with DTrace Object allocation, Memory management, file access, graphics - Versatile performance profiling - Powerful analysis - Fully understand the context of your data
Xcode Apple&#x2019;s IDE for building OS X, iPhone OS, Mac apps, iPhone Apps 3 SDK releases - Mac, iPhone, iPad app develpment (>2GB downloads) Interface Builder Prototyping and Implementation Tool - Graphically layout your interfaces - connect your interface to your code Iphone simulator Rapid prototyping and deployment iPhone API implementation on Intel hardware (not a hardware emulator) Instruments Performance analysis Tool Built with DTrace Object allocation, Memory management, file access, graphics - Versatile performance profiling - Powerful analysis - Fully understand the context of your data
Xcode Apple&#x2019;s IDE for building OS X, iPhone OS, Mac apps, iPhone Apps 3 SDK releases - Mac, iPhone, iPad app develpment (>2GB downloads) Interface Builder Prototyping and Implementation Tool - Graphically layout your interfaces - connect your interface to your code Iphone simulator Rapid prototyping and deployment iPhone API implementation on Intel hardware (not a hardware emulator) Instruments Performance analysis Tool Built with DTrace Object allocation, Memory management, file access, graphics - Versatile performance profiling - Powerful analysis - Fully understand the context of your data
Xcode Apple&#x2019;s IDE for building OS X, iPhone OS, Mac apps, iPhone Apps 3 SDK releases - Mac, iPhone, iPad app develpment (>2GB downloads) Interface Builder Prototyping and Implementation Tool - Graphically layout your interfaces - connect your interface to your code Iphone simulator Rapid prototyping and deployment iPhone API implementation on Intel hardware (not a hardware emulator) Instruments Performance analysis Tool Built with DTrace Object allocation, Memory management, file access, graphics - Versatile performance profiling - Powerful analysis - Fully understand the context of your data
Xcode Apple&#x2019;s IDE for building OS X, iPhone OS, Mac apps, iPhone Apps 3 SDK releases - Mac, iPhone, iPad app develpment (>2GB downloads) Interface Builder Prototyping and Implementation Tool - Graphically layout your interfaces - connect your interface to your code Iphone simulator Rapid prototyping and deployment iPhone API implementation on Intel hardware (not a hardware emulator) Instruments Performance analysis Tool Built with DTrace Object allocation, Memory management, file access, graphics - Versatile performance profiling - Powerful analysis - Fully understand the context of your data
Xcode Apple&#x2019;s IDE for building OS X, iPhone OS, Mac apps, iPhone Apps 3 SDK releases - Mac, iPhone, iPad app develpment (>2GB downloads) Interface Builder Prototyping and Implementation Tool - Graphically layout your interfaces - connect your interface to your code Iphone simulator Rapid prototyping and deployment iPhone API implementation on Intel hardware (not a hardware emulator) Instruments Performance analysis Tool Built with DTrace Object allocation, Memory management, file access, graphics - Versatile performance profiling - Powerful analysis - Fully understand the context of your data
Xcode Apple&#x2019;s IDE for building OS X, iPhone OS, Mac apps, iPhone Apps 3 SDK releases - Mac, iPhone, iPad app develpment (>2GB downloads) Interface Builder Prototyping and Implementation Tool - Graphically layout your interfaces - connect your interface to your code Iphone simulator Rapid prototyping and deployment iPhone API implementation on Intel hardware (not a hardware emulator) Instruments Performance analysis Tool Built with DTrace Object allocation, Memory management, file access, graphics - Versatile performance profiling - Powerful analysis - Fully understand the context of your data
Xcode Apple&#x2019;s IDE for building OS X, iPhone OS, Mac apps, iPhone Apps 3 SDK releases - Mac, iPhone, iPad app develpment (>2GB downloads) Interface Builder Prototyping and Implementation Tool - Graphically layout your interfaces - connect your interface to your code Iphone simulator Rapid prototyping and deployment iPhone API implementation on Intel hardware (not a hardware emulator) Instruments Performance analysis Tool Built with DTrace Object allocation, Memory management, file access, graphics - Versatile performance profiling - Powerful analysis - Fully understand the context of your data
Xcode Apple&#x2019;s IDE for building OS X, iPhone OS, Mac apps, iPhone Apps 3 SDK releases - Mac, iPhone, iPad app develpment (>2GB downloads) Interface Builder Prototyping and Implementation Tool - Graphically layout your interfaces - connect your interface to your code Iphone simulator Rapid prototyping and deployment iPhone API implementation on Intel hardware (not a hardware emulator) Instruments Performance analysis Tool Built with DTrace Object allocation, Memory management, file access, graphics - Versatile performance profiling - Powerful analysis - Fully understand the context of your data
Xcode Apple&#x2019;s IDE for building OS X, iPhone OS, Mac apps, iPhone Apps 3 SDK releases - Mac, iPhone, iPad app develpment (>2GB downloads) Interface Builder Prototyping and Implementation Tool - Graphically layout your interfaces - connect your interface to your code Iphone simulator Rapid prototyping and deployment iPhone API implementation on Intel hardware (not a hardware emulator) Instruments Performance analysis Tool Built with DTrace Object allocation, Memory management, file access, graphics - Versatile performance profiling - Powerful analysis - Fully understand the context of your data
Xcode Apple&#x2019;s IDE for building OS X, iPhone OS, Mac apps, iPhone Apps 3 SDK releases - Mac, iPhone, iPad app develpment (>2GB downloads) Interface Builder Prototyping and Implementation Tool - Graphically layout your interfaces - connect your interface to your code Iphone simulator Rapid prototyping and deployment iPhone API implementation on Intel hardware (not a hardware emulator) Instruments Performance analysis Tool Built with DTrace Object allocation, Memory management, file access, graphics - Versatile performance profiling - Powerful analysis - Fully understand the context of your data
Xcode Apple&#x2019;s IDE for building OS X, iPhone OS, Mac apps, iPhone Apps 3 SDK releases - Mac, iPhone, iPad app develpment (>2GB downloads) Interface Builder Prototyping and Implementation Tool - Graphically layout your interfaces - connect your interface to your code Iphone simulator Rapid prototyping and deployment iPhone API implementation on Intel hardware (not a hardware emulator) Instruments Performance analysis Tool Built with DTrace Object allocation, Memory management, file access, graphics - Versatile performance profiling - Powerful analysis - Fully understand the context of your data

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Editor's Notes